{"schema_version":"onlylabs.public_analysis_evidence.v1","title":"Cerebras analysis evidence pack","description":"Public onlylabs evidence pack for cited agent analysis: captured pages, ranked public signals, and stored web-search provenance used by the background analysis workflow.","url":"https://onlylabs.fyi/labs/cerebras","json_url":"https://onlylabs.fyi/analysis/cerebras/evidence.json","generated_at":"2026-06-11T18:08:18.949Z","org":{"slug":"cerebras","name":"Cerebras","category":"neocloud","category_label":"Neocloud","dossier_url":"https://onlylabs.fyi/labs/cerebras"},"analysis":null,"workflow":{"version":"onlylabs-deepagents-analysis-v3","provider":null,"model":null,"agent":null,"public_pack_mode":"local-pages-and-events","live_web_fetches":false,"note":"Public evidence exports do not trigger live Exa calls; stored Exa provenance is included when analysis metadata contains it."},"stats":{"pages":28,"events":140,"web":0,"evidence":88,"signal_desks":{"hiring":48,"forks":0,"releases":12,"talking":0,"repos":0},"data_radar_lanes":null,"data_radar_matches":null,"stored_analysis_evidence":null,"stored_analysis_web":null,"stored_analysis_signal_desks":null,"stored_analysis_data_radar_lanes":null,"stored_analysis_data_radar_matches":null},"stored_web_provenance":null,"evidence":[{"ref":"P1","kind":"page","title":"Cerebras/open-register-design-tool repository metadata","date":"2026-06-11T04:19:33.880632+00:00","date_source":null,"source_url":"https://github.com/Cerebras/open-register-design-tool","signal_url":null,"signal_json_url":null,"text":"# Cerebras/open-register-design-tool\n\nDescription: Tool to generate register RTL, models, and docs using SystemRDL or JSpec input\n\nLanguage: Verilog\n\nLicense: Apache-2.0\n\nStars: 1\n\nForks: 1\n\nOpen issues: 0\n\nCreated: 2017-11-08T21:35:30Z\n\nPushed: 2026-04-06T16:58:33Z\n\nDefault branch: master\n\nFork: yes\n\nParent repository: Juniper/open-register-design-tool\n\nArchived: no\n\nREADME:\n# open-register-design-tool\n\nOrdt is a tool for automation of IC register definition and documentation. It currently supports 2 input formats:\n1. SystemRDL - a stardard register description format released by [Accellera.org](http://accellera.org/activities/working-groups/systemrdl)\n2. JSpec - a register description format used within Juniper Networks\n\nThe tool can generate several outputs from SystemRDL or JSpec, including:\n- SystemVerilog/Verilog RTL code description of registers\n- UVM model of the registers\n- C++ and python models of the registers\n- XML and text file register descriptions\n- SystemRDL and JSpec (conversion)\n\nEasiest way to get started with ordt is to download a runnable jar from the [release area](https://github.com/Juniper/open-register-design-tool/releases). \nOrdt documentation can be found [here](https://github.com/Juniper/open-register-design-tool/wiki)."},{"ref":"P2","kind":"page","title":"Cerebras/libtins repository metadata","date":"2026-06-11T04:19:33.746076+00:00","date_source":null,"source_url":"https://github.com/Cerebras/libtins","signal_url":null,"signal_json_url":null,"text":"# Cerebras/libtins\n\nDescription: High-level, multiplatform C++ network packet sniffing and crafting library. \n\nLanguage: C++\n\nLicense: BSD-2-Clause\n\nStars: 4\n\nForks: 3\n\nOpen issues: 0\n\nCreated: 2017-12-10T03:13:11Z\n\nPushed: 2024-10-10T23:34:35Z\n\nDefault branch: master\n\nFork: yes\n\nParent repository: mfontanini/libtins\n\nArchived: no\n\nREADME:\n# libtins\n\n[![Build status](https://travis-ci.org/mfontanini/libtins.svg?branch=master)](https://travis-ci.org/mfontanini/libtins) \n[![Build status](https://ci.appveyor.com/api/projects/status/33n8ib68nx3tptib/branch/master?svg=true)](https://ci.appveyor.com/project/mfontanini/libtins/branch/master)\n\nlibtins is a high-level, multiplatform C++ network packet sniffing and \ncrafting library. \n\nIts main purpose is to provide the C++ developer an easy, efficient, \nplatform and endianess-independent way to create tools which need to \nsend, receive and manipulate specially crafted packets. \n\nIn order to read tutorials, examples and checkout some benchmarks of the\nlibrary, please visit:\n\nhttp://libtins.github.io/\n\n## Compiling ##\n\n[libtins](http://libtins.github.io/) depends on \n[libpcap](http://www.tcpdump.org/) and \n[openssl](http://www.openssl.org/), although the latter is not necessary \nif some features of the library are disabled.\n\nIn order to compile, execute:\n\n```Shell\n# Create the build directory\nmkdir build\ncd build\n\n# Configure the project. Add any relevant configuration flags\ncmake ../\n\n# Compile!\nmake\n```\n\n### Static/shared build\nNote that by default, only the shared object is compiled. If you would\nlike to generate a static library file, run:\n\n```Shell\ncmake ../ -DLIBTINS_BUILD_SHARED=0\n```\n\nThe generated static/shared library files will be located in the \n_build/lib_ directory.\n\n### C++11 support\n\nlibtins is noticeably faster if you enable _C++11_ support. Therefore, \nif your compiler supports this standard, then you should enable it. \nIn order to do so, use the _LIBTINS_ENABLE_CXX11_ switch:\n\n```Shell\ncmake ../ -DLIBTINS_ENABLE_CXX11=1\n```\n\n### TCP ACK tracker\n\nThe TCP ACK tracker feature requires the boost.icl library (header only).\nThis feature is enabled by default but will be disabled if the boost\nheaders are not fo"},{"ref":"P3","kind":"page","title":"Cerebras/g3log repository metadata","date":"2026-06-11T04:19:33.587212+00:00","date_source":null,"source_url":"https://github.com/Cerebras/g3log","signal_url":null,"signal_json_url":null,"text":"# Cerebras/g3log\n\nDescription: G3log is an asynchronous, \"crash safe\", logger that is easy to use with default logging sinks or you can add your own. G3log is made with plain C++11 with no external libraries (except gtest used for unit tests). G3log is made to be cross-platform, currently running on OSX, Windows and several Linux distros. See Readme below for details of usage.\n\nLanguage: C++\n\nLicense: Unlicense\n\nStars: 2\n\nForks: 3\n\nOpen issues: 0\n\nCreated: 2018-03-19T16:01:54Z\n\nPushed: 2021-02-07T06:04:27Z\n\nDefault branch: master\n\nFork: yes\n\nParent repository: KjellKod/g3log\n\nArchived: no\n\nREADME:\n# G3log : Asynchronous logger with Dynamic Sinks\n\n## EXAMPLE USAGE\n#### Optional to use either streaming or printf-like syntax\n```\nLOG(INFO) << \"streaming API is as easy as ABC or \" << 123;\n\nLOGF(WARNING, \"Printf-style syntax is also %s\", \"available\");\n```\n\n#### Conditional logging\nint less = 1; int more = 2\nLOG_IF(INFO, (less<more)) <<\"If [true], then this text will be logged\";\n\n// or with printf-like syntax\nLOGF_IF(INFO, (less<more), \"if %d<%d then this text will be logged\", less,more);\n\n#### Design-by-Contract\n*CHECK(false)* will trigger a \"fatal\" message. It will be logged, and then the \napplication will exit.\n\n```\nCHECK(less != more); // not FATAL\nCHECK(less > more) << \"CHECK(false) triggers a FATAL message\";\n```\n\n## What G3Log is: \n* ***G3log*** is the acting name for the third version of g2log and it stands for **g3log with dynamic sinks**\n* G3log is an asynchronous, \"crash-safe\" logger. You can read more about it here [[g2log version]](\nhttp://www.codeproject.com/Articles/288827/g2log-An-efficient-asynchronous-logger-using-Cplus)\n* You can choose to use the default log receiver which saves all LOG calls to file, **or** you can choose to use your own custom made log receiver(s), **or** both, **or** as many sinks as you need.\n\n## Detailed API documentation\nPlease look at [API.markdown](API.markdown) for detailed API documentation\n\n## Benefits you get when using G3log ##\n1. Easy to use, clean syntax and a blazing fast logger. \n\n2. All the slow log I/O disk access is done in a background thread. This ensures that the LOG caller can immediately continue with other t"},{"ref":"P4","kind":"page","title":"Cerebras/tensorflow repository metadata","date":"2026-06-11T04:19:33.466247+00:00","date_source":null,"source_url":"https://github.com/Cerebras/tensorflow","signal_url":null,"signal_json_url":null,"text":"# Cerebras/tensorflow\n\nDescription: An Open Source Machine Learning Framework for Everyone\n\nLanguage: C++\n\nLicense: Apache-2.0\n\nStars: 2\n\nForks: 4\n\nOpen issues: 0\n\nCreated: 2019-02-05T20:16:22Z\n\nPushed: 2020-05-07T22:07:20Z\n\nDefault branch: master\n\nFork: yes\n\nParent repository: tensorflow/tensorflow\n\nArchived: no\n\nREADME:\n<div align=\"center\">\n<img src=\"https://www.tensorflow.org/images/tf_logo_social.png\">\n</div>\n\n[![Python](https://img.shields.io/pypi/pyversions/tensorflow.svg?style=plastic)](https://badge.fury.io/py/tensorflow)\n[![PyPI](https://badge.fury.io/py/tensorflow.svg)](https://badge.fury.io/py/tensorflow)\n\n**`Documentation`** |\n------------------- |\n[![Documentation](https://img.shields.io/badge/api-reference-blue.svg)](https://www.tensorflow.org/api_docs/) |\n\n[TensorFlow](https://www.tensorflow.org/) is an end-to-end open source platform\nfor machine learning. It has a comprehensive, flexible ecosystem of\n[tools](https://www.tensorflow.org/resources/tools),\n[libraries](https://www.tensorflow.org/resources/libraries-extensions), and\n[community](https://www.tensorflow.org/community) resources that lets\nresearchers push the state-of-the-art in ML and developers easily build and\ndeploy ML-powered applications.\n\nTensorFlow was originally developed by researchers and engineers working on the\nGoogle Brain team within Google's Machine Intelligence Research organization to\nconduct machine learning and deep neural networks research. The system is\ngeneral enough to be applicable in a wide variety of other domains, as well.\n\nTensorFlow provides stable [Python](https://www.tensorflow.org/api_docs/python)\nand [C++](https://www.tensorflow.org/api_docs/cc) APIs, as well as\nnon-guaranteed backward compatible API for\n[other languages](https://www.tensorflow.org/api_docs).\n\nKeep up-to-date with release announcements and security updates by subscribing\nto\n[announce@tensorflow.org](https://groups.google.com/a/tensorflow.org/forum/#!forum/announce).\nSee all the [mailing lists](https://www.tensorflow.org/community/forums).\n\n## Install\n\nSee the [TensorFlow install guide](https://www.tensorflow.org/install) for the\n[pip package](https://www.tensorflow.org/install/pip), to\n[en"},{"ref":"P5","kind":"page","title":"Cerebras/aws-parallelcluster-node repository metadata","date":"2026-06-11T04:19:33.454897+00:00","date_source":null,"source_url":"https://github.com/Cerebras/aws-parallelcluster-node","signal_url":null,"signal_json_url":null,"text":"# Cerebras/aws-parallelcluster-node\n\nDescription: aws-parallelcluster-node is the python package installed on the Amazon EC2 instances launched as part of AWS ParallelCluster\n\nLicense: Apache-2.0\n\nStars: 2\n\nForks: 1\n\nOpen issues: 0\n\nCreated: 2019-10-03T04:05:38Z\n\nPushed: 2020-06-18T23:30:07Z\n\nDefault branch: develop\n\nFork: yes\n\nParent repository: aws/aws-parallelcluster-node\n\nArchived: yes\n\nREADME:\n========================\nAWS ParallelCluster Node\n========================\n\n|Build Status| |Version|\n\n.. |Build Status| image:: https://travis-ci.org/aws/aws-parallelcluster-node.png?branch=develop\n:target: https://travis-ci.org/aws/aws-parallelcluster-node/\n:alt: Build Status\n.. |Version| image:: https://badge.fury.io/py/aws-parallelcluster-node.png\n:target: https://badge.fury.io/py/aws-parallelcluster-node\n\nThis repo contains the aws-parallelcluster-node package installed on the Amazon EC2 instances launched\nas part of AWS ParallelCluster."},{"ref":"P6","kind":"page","title":"Cerebras/archivemount repository metadata","date":"2026-06-11T04:19:33.110052+00:00","date_source":null,"source_url":"https://github.com/Cerebras/archivemount","signal_url":null,"signal_json_url":null,"text":"# Cerebras/archivemount\n\nDescription: A fuse filesystem for mounting archives in formats supported by libarchive.\n\nLicense: NOASSERTION\n\nStars: 1\n\nForks: 1\n\nOpen issues: 0\n\nCreated: 2020-04-15T17:50:40Z\n\nPushed: 2020-04-16T06:33:31Z\n\nDefault branch: master\n\nFork: yes\n\nParent repository: ebertland/archivemount\n\nArchived: no\n\nREADME:\nWhat is it\n----------\nArchivemount is a piece of glue code between libarchive\n(http://people.freebsd.org/~kientzle/libarchive/) and FUSE\n(http://fuse.sourceforge.net). It can be used to mount a (possibly compressed)\narchive (as in .tar.gz or .tar.bz2) and use it like an ordinary filesystem.\n\nRequirements\n------------\nYou will need autoconf, libarchive-dev and libfuse-dev for building\narchivemont, as well as GNU make and gcc of course.\n\nInstallation\n------------\nFrom version 0.6.0 on archivemount uses autoconf, so just do the normal\n\nautoreconf -i\n./configure && make && sudo make install\n\nto build archivemount and install it to /usr/local. For building it,\nlibfuse is needed in version 2.6 or higher, including its headerfiles\nof course (on most distributions those can be found in a package named\nsomething like libfuse-dev or so).\n\nUsage\n-----\narchivemount <options> <archive> <mountpoint>\nOptions are the normal fuse mount options, nothing special supported yet.\n\nWrite support\n-------------\nWriting to an archive with libarchive is unfortunately not possible. In\norder to provide write support thus the whole archive has to be recreated;\nthis requires two things: space and time. To optimize at least the timely\nbehaviour, archives are recreated only once: at the time of unmount. If there\nare any problems creating the new archive - bad luck, the changes are lost. Some\nchecks are run when mounting the archive to determine if it can be mounted\nwriteable, but there is no guarantee.\nAlso note that unmounting a fuse filesystem is NOT necessarily completed when\nthe unmount command returns. Although unmounting takes a long time already,\nfuse backgrounds the process and lets the unmount command return early. You\ncan check on the real state of unmounting by checking the process list for\narchivemount.\n\nTHERE IS ALSO NO GUARANTEE THAT DATA IS WRITTEN COR"},{"ref":"P7","kind":"page","title":"Cerebras/modelzoo-staging repository metadata","date":"2026-06-11T04:19:32.726791+00:00","date_source":null,"source_url":"https://github.com/Cerebras/modelzoo-staging","signal_url":null,"signal_json_url":null,"text":"# Cerebras/modelzoo-staging\n\nLanguage: Python\n\nLicense: Apache-2.0\n\nStars: 0\n\nForks: 0\n\nOpen issues: 0\n\nCreated: 2023-03-28T13:02:42Z\n\nPushed: 2026-03-10T15:16:43Z\n\nDefault branch: main\n\nFork: yes\n\nParent repository: Cerebras/modelzoo\n\nArchived: no\n\nREADME:\n# Cerebras Model Zoo\n\n## Introduction\n\nThis repository contains examples of common deep learning models that can be trained on Cerebras hardware. These models demonstrate the best practices for coding a model targeted at the Cerebras hardware so that you can take full advantage of this new powerful compute engine.\n\nIn order to get started with running your models on a Cerebras system, please refer to the [Developer Documentation](https://docs.cerebras.net/en/latest/index.html) along with this readme.\n\n**NOTE**: If you are interested in trying out Cerebras Model Zoo on Cerebras Hardware (CS-2 Systems), we offer the following options:\n\n- Academics - Please fill out our Partner Hardware Access Request form [here](https://www.cerebras.net/developers/partner-hardware-access-request/) and we will contact you about gaining access to a system from one of our partners.\n- Commercial - Please fill out our Get Demo form [here]( https://www.cerebras.net/get-demo/) so that our team can provide you with a demo and discuss access to our system.\n- For all others - Please contact us at developer@cerebras.net.\n\nFor a list of all supported models, please check [models in this repository](#models-in-this-repository).\n\n## Installation\n\nTo install the Cerebras Model Zoo on the CSX system, please follow the instructions in [PYTHON-SETUP.md](./PYTHON-SETUP.md).\n\n## Supported frameworks\n\nWe support the models developed in [PyTorch](https://pytorch.org/).\n\n## Basic workflow\n\nWhen you are targeting the Cerebras Wafer-Scale Cluster for your neural network jobs, please follow the [quick start guide](https://docs.cerebras.net/en/latest/wsc/getting-started/cs-appliance.html) from the developer docs to compile, validate and train the models in this Model Zoo for the framework of your choice.\n\nFor advanced use cases and porting your existing code please refer to the [developer docs](https://docs.cerebras.net/en/latest/wsc/port/index.html).\n\n#"},{"ref":"P8","kind":"page","title":"Senior ML Systems Engineer","date":"2026-06-11T04:13:49.679005+00:00","date_source":null,"source_url":"https://job-boards.greenhouse.io/cerebrassystems/jobs/7622330003","signal_url":null,"signal_json_url":null,"text":"Job Application for Senior ML Systems Engineer at Cerebras Systems \n\nBack to jobs \nSenior ML Systems Engineer\nSunnyvale CA or Toronto Canada\n\nApply \nCerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. Our novel wafer-scale architecture provides the AI compute power of dozens of GPUs on a single chip, with the programming simplicity of a single device. This approach allows Cerebras to deliver industry-leading training and inference speeds and empowers machine learning users to effortlessly run large-scale ML applications, without the hassle of managing hundreds of GPUs or TPUs. \n\nCerebras' current customers include top model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras , to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference. \n\nThanks to the groundbreaking wafer-scale architecture, Cerebras Inference offers the fastest Generative AI inference solution in the world, over 10 times faster than GPU-based hyperscale cloud inference services. This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nAbout the Role \nWe are seeking a versatile and experienced engineer to join our SOTA Training Platform team. This team is responsible to rapidly bring up state-of-the-art open-source models (like LLaMA, Qwen, etc) or customer-provided proprietary models on our Cerebras CSX systems. Success in this role requires a system-minded generalist who thrives in fast-paced bringup environments and is comfortable working across the entire Cerebras software stack.\nYour work will play a critical role in achieving unprecedented levels of performance, efficiency, and scalability for AI applications.\n\nResponsibilities \n\nContribute to the end-to-end bring up of ML models on Cerebras CSX systems.\n\nWork across the stack: model architecture translation, graph lowering, compiler optimizations, runtime integration, and performance tuning.\n\nDebug performance and correctness issues spanning model code, compiler IRs, ru"},{"ref":"P9","kind":"page","title":"ML Software Tool Development Engineer","date":"2026-06-11T04:13:49.483433+00:00","date_source":null,"source_url":"https://job-boards.greenhouse.io/cerebrassystems/jobs/7634141003","signal_url":null,"signal_json_url":null,"text":"Job Application for ML Software Tool Development Engineer at Cerebras Systems \n\nBack to jobs \nML Software Tool Development Engineer\nSunnyvale CA or Toronto Canada\n\nApply \nCerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. Our novel wafer-scale architecture provides the AI compute power of dozens of GPUs on a single chip, with the programming simplicity of a single device. This approach allows Cerebras to deliver industry-leading training and inference speeds and empowers machine learning users to effortlessly run large-scale ML applications, without the hassle of managing hundreds of GPUs or TPUs. \n\nCerebras' current customers include top model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras , to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference. \n\nThanks to the groundbreaking wafer-scale architecture, Cerebras Inference offers the fastest Generative AI inference solution in the world, over 10 times faster than GPU-based hyperscale cloud inference services. This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nResponsibilities: \n\nLead the design and implementation of system-level debugging, validation, and observability platforms.\n\nDevelop automated systems for collecting and analyzing numerical, and execution anomalies.\n\nCreate visualization and analysis tools to enable efficient root-cause investigation.\n\nBuild frameworks for failure classification, regression detection, and anomaly monitoring.\n\nExtend compilers, runtimes, and programming interfaces to support advanced profiling and instrumentation.\n\nImprove system bring-up, low-level debug, and validation workflows.\n\nPartner cross-functionally with compiler, hardware, firmware, runtime, and infrastructure teams.\n\nEstablish best practices for debuggability, reliability, and operational excellence.\n\nLead high-impact initiatives.\n\nSupport incident response and drive long-term corrective actions.\n\nQualifications: \n\nStrong proficie"},{"ref":"P10","kind":"page","title":"Performance & Reliability Engineer","date":"2026-06-11T04:13:49.435982+00:00","date_source":null,"source_url":"https://job-boards.greenhouse.io/cerebrassystems/jobs/7528266003","signal_url":null,"signal_json_url":null,"text":"Job Application for Performance & Reliability Engineer at Cerebras Systems \n\nBack to jobs \nPerformance & Reliability Engineer\nSunnyvale, CA; Toronto, Ontario, Canada\n\nApply \nCerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. Our novel wafer-scale architecture provides the AI compute power of dozens of GPUs on a single chip, with the programming simplicity of a single device. This approach allows Cerebras to deliver industry-leading training and inference speeds and empowers machine learning users to effortlessly run large-scale ML applications, without the hassle of managing hundreds of GPUs or TPUs. \n\nCerebras' current customers include top model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras , to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference. \n\nThanks to the groundbreaking wafer-scale architecture, Cerebras Inference offers the fastest Generative AI inference solution in the world, over 10 times faster than GPU-based hyperscale cloud inference services. This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nAbout The Role \n\nJoin Cerebras as a Performance & Reliability Engineer within our innovative Co-Design and Next Generation Team. Our groundbreaking CS-3 system has set new benchmarks in high-performance ML training and inference solutions. It leverages a dinner-plate sized chip with 44GB of on-chip memory to surpass traditional hardware capabilities. This role focuses on characterizing and optimizing the performance and reliability of state-of-the-art AI models running on Cerebras' breakthrough hardware.\n\nResponsibilities \n\nCharacterize and enhance the performance and reliability of advanced ML hardware/software systems, with emphasis on reducing power and thermal fluctuations.\n\nAnalyze ML workloads, software kernels, and hardware architecture for power and performance impacts, and synthesize high-level insights across these layers.\n\nDevelop creative software solutions t"},{"ref":"P11","kind":"page","title":"Kernel Engineer","date":"2026-06-11T04:13:49.353731+00:00","date_source":null,"source_url":"https://job-boards.greenhouse.io/cerebrassystems/jobs/7618093003","signal_url":null,"signal_json_url":null,"text":"Job Application for Kernel Engineer at Cerebras Systems \n\nBack to jobs \nKernel Engineer\nSunnyvale CA or Toronto Canada\n\nApply \nCerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. Our novel wafer-scale architecture provides the AI compute power of dozens of GPUs on a single chip, with the programming simplicity of a single device. This approach allows Cerebras to deliver industry-leading training and inference speeds and empowers machine learning users to effortlessly run large-scale ML applications, without the hassle of managing hundreds of GPUs or TPUs. \n\nCerebras' current customers include top model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras , to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference. \n\nThanks to the groundbreaking wafer-scale architecture, Cerebras Inference offers the fastest Generative AI inference solution in the world, over 10 times faster than GPU-based hyperscale cloud inference services. This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nAbout The Role \n\nAs a Kernel Engineer on our team, you will develop high-performance software solutions at the intersection of hardware and software, developing high-performance software for cutting-edge AI and HPC workloads. Your focus will be on implementing, optimizing, and scaling deep learning operations to fully leverage our custom, massively parallel processor architecture. \n\nYou will be part of a world-class team responsible for the design, performance tuning, and validation of foundational ML and HPC kernels. This includes building a library of parallel and distributed algorithms that maximize compute utilization and push the boundaries of training efficiency for state-of-the-art AI models. Your work will be critical to unlocking the full potential of our hardware and accelerating the pace of AI innovation.\n\nResponsibilities \n\nDevelop design specifications for new machine learning and linear algebra kernels "},{"ref":"P12","kind":"page","title":"Kernel Engineer","date":"2026-06-11T04:13:49.284106+00:00","date_source":null,"source_url":"https://job-boards.greenhouse.io/cerebrassystems/jobs/7486714003","signal_url":null,"signal_json_url":null,"text":"Job Application for Kernel Engineer at Cerebras Systems \n\nBack to jobs \nKernel Engineer\nBengaluru, Karnataka, India\n\nApply \nCerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. Our novel wafer-scale architecture provides the AI compute power of dozens of GPUs on a single chip, with the programming simplicity of a single device. This approach allows Cerebras to deliver industry-leading training and inference speeds and empowers machine learning users to effortlessly run large-scale ML applications, without the hassle of managing hundreds of GPUs or TPUs. \n\nCerebras' current customers include top model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras , to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference. \n\nThanks to the groundbreaking wafer-scale architecture, Cerebras Inference offers the fastest Generative AI inference solution in the world, over 10 times faster than GPU-based hyperscale cloud inference services. This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nAbout The Role\n\nAs a Kernel Engineer on our team, you will develop high-performance software solutions at the intersection of hardware and software, developing high-performance software for cutting-edge AI and HPC workloads. Your focus will be on implementing, optimizing, and scaling deep learning operations to fully leverage our custom, massively parallel processor architecture.\n\nYou will be part of a world-class team responsible for the design, performance tuning, and validation of foundational ML and HPC kernels. This includes building a library of parallel and distributed algorithms that maximize compute utilization and push the boundaries of training efficiency for state-of-the-art AI models. Your work will be critical to unlocking the full potential of our hardware and accelerating the pace of AI innovation.\n\nResponsibilities \n\nDevelop design specifications for new machine learning and linear algebra kernels and m"},{"ref":"P13","kind":"page","title":"Senior GL Accountant","date":"2026-06-11T04:13:49.247698+00:00","date_source":null,"source_url":"https://job-boards.greenhouse.io/cerebrassystems/jobs/7694944003","signal_url":null,"signal_json_url":null,"text":"Job Application for Senior GL Accountant at Cerebras Systems \n\nBack to jobs \nSenior GL Accountant\nSunnyvale, CA\n\nApply \nCerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. Our novel wafer-scale architecture provides the AI compute power of dozens of GPUs on a single chip, with the programming simplicity of a single device. This approach allows Cerebras to deliver industry-leading training and inference speeds and empowers machine learning users to effortlessly run large-scale ML applications, without the hassle of managing hundreds of GPUs or TPUs. \n\nCerebras' current customers include top model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras , to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference. \n\nThanks to the groundbreaking wafer-scale architecture, Cerebras Inference offers the fastest Generative AI inference solution in the world, over 10 times faster than GPU-based hyperscale cloud inference services. This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nAbout The Role \n\nWe are seeking a detail-oriented and experienced Senior GL Accountant to join our corporate accounting team. This role is responsible for participating and maintaining general ledger accounting operations, ensuring accurate and timely financial reporting in compliance with U.S. GAAP.\n\nResponsibilities \n\nPerform the monthly, quarterly, and annual financial statement close processes globally in accordance with US GAAP, including preparation and review of journal entries, account reconciliations, and variance analysis for cash, prepaids, accruals, inter-company, OPEX and various other accounts.\n\nSupport the external reporting function by providing account reconciliation and analysis reports for statements of cash flow and financial statement footnotes and disclosures preparation.\n\nSupport quarterly, annual and interim external audits including preparation of audit schedules and responding to auditor requests.\n"},{"ref":"P14","kind":"page","title":"Full Stack Engineer – Manufacturing Test ","date":"2026-06-11T04:13:49.023909+00:00","date_source":null,"source_url":"https://job-boards.greenhouse.io/cerebrassystems/jobs/7628224003","signal_url":null,"signal_json_url":null,"text":"Job Application for Full Stack Engineer – Manufacturing Test at Cerebras Systems \n\nBack to jobs \nFull Stack Engineer – Manufacturing Test \nSunnyvale, CA\n\nApply \nCerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. Our novel wafer-scale architecture provides the AI compute power of dozens of GPUs on a single chip, with the programming simplicity of a single device. This approach allows Cerebras to deliver industry-leading training and inference speeds and empowers machine learning users to effortlessly run large-scale ML applications, without the hassle of managing hundreds of GPUs or TPUs. \n\nCerebras' current customers include top model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras , to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference. \n\nThanks to the groundbreaking wafer-scale architecture, Cerebras Inference offers the fastest Generative AI inference solution in the world, over 10 times faster than GPU-based hyperscale cloud inference services. This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nAbout the Role \n\nAs a Full Stack Engineer focusing on Cerebras’ manufacturing test platform, you will design, build, and maintain a comprehensive test software solution for all stages of manufacturing – from individual components to complete Cerebras systems. You will collaborate cross-functionally with hardware design, engineering, operations, and data analytics teams to develop user interfaces and data processing frameworks that directly impact manufacturing efficiency, quality, and scalability. \n\nResponsibilities \n\nCollaborate with hardware engineers and test developers to create frameworks that facilitate the development, validation, and deployment of manufacturing tests. \n\nCreate an intuitive, functional, and flexible user interface for executing a wide variety of manufacturing tests. \n\nCreate a distributed data storage framework to sync test data across multiple manufacturing f"},{"ref":"P15","kind":"page","title":"Vice President, Creative & Integrated Marketing ","date":"2026-06-11T04:13:48.954281+00:00","date_source":null,"source_url":"https://job-boards.greenhouse.io/cerebrassystems/jobs/7628240003","signal_url":null,"signal_json_url":null,"text":"Job Application for Vice President, Creative & Integrated Marketing at Cerebras Systems \n\nBack to jobs \nVice President, Creative & Integrated Marketing \nSunnyvale, CA\n\nApply \nCerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. Our novel wafer-scale architecture provides the AI compute power of dozens of GPUs on a single chip, with the programming simplicity of a single device. This approach allows Cerebras to deliver industry-leading training and inference speeds and empowers machine learning users to effortlessly run large-scale ML applications, without the hassle of managing hundreds of GPUs or TPUs. \n\nCerebras' current customers include top model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras , to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference. \n\nThanks to the groundbreaking wafer-scale architecture, Cerebras Inference offers the fastest Generative AI inference solution in the world, over 10 times faster than GPU-based hyperscale cloud inference services. This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nAbout The Role\n\nWe are seeking a dynamic Vice President of Creative & Integrated Marketing to lead brand expression and orchestrate high-impact, cross-channel marketing programs that drive awareness, engagement, and pipeline growth. \n\nReporting to the CMO, this leader will unify creative excellence with integrated go-to-market execution — ensuring that every campaign, launch, and brand moment is cohesive, differentiated, and performance-oriented. \n\nThis role blends visionary brand leadership with operational rigor, connecting storytelling to measurable business outcomes. \n\nResponsibilities \n\nCreative & Brand Leadership \n\nOwn the company’s creative vision and brand expression across all channels. \n\nEnsure consistent, differentiated storytelling across corporate, product, and executive communications. \n\nMaintain a high bar for design, copy, video, experiential, and digita"},{"ref":"P16","kind":"page","title":"Director of Costing Accounting","date":"2026-06-11T04:13:48.823093+00:00","date_source":null,"source_url":"https://job-boards.greenhouse.io/cerebrassystems/jobs/7579627003","signal_url":null,"signal_json_url":null,"text":"Job Application for Director of Costing Accounting at Cerebras Systems \n\nBack to jobs \nDirector of Costing Accounting\nSunnyvale, CA\n\nApply \nCerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. Our novel wafer-scale architecture provides the AI compute power of dozens of GPUs on a single chip, with the programming simplicity of a single device. This approach allows Cerebras to deliver industry-leading training and inference speeds and empowers machine learning users to effortlessly run large-scale ML applications, without the hassle of managing hundreds of GPUs or TPUs. \n\nCerebras' current customers include top model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras , to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference. \n\nThanks to the groundbreaking wafer-scale architecture, Cerebras Inference offers the fastest Generative AI inference solution in the world, over 10 times faster than GPU-based hyperscale cloud inference services. This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nAbout The Role\n\nThe Director of Cost Accounting will lead all cost accounting, inventory, and cost-related financial activities across manufacturing, infrastructure, and AI compute operations. This role is critical to ensuring accurate costing, capitalized asset accounting, and cost transparency across both training and inference workloads.\n\nThis role requires comfort operating in a fast-paced, evolving environment, where priorities may shift and processes are still being built. The successful candidate will be expected to ramp quickly, close gaps, and contribute immediately, bringing structure, judgment, and execution while helping where needed across the broader finance organization.\n\nYou will partner closely with Manufacturing, Supply Chain, FP&A, Deployment, and Engineering to establish scalable costing models, strengthen controls, and support external reporting readiness as the company prepares to o"},{"ref":"P17","kind":"page","title":"System Software Engineer (Embedded)","date":"2026-06-11T04:13:48.805434+00:00","date_source":null,"source_url":"https://job-boards.greenhouse.io/cerebrassystems/jobs/7628229003","signal_url":null,"signal_json_url":null,"text":"Job Application for System Software Engineer (Embedded) at Cerebras Systems \n\nBack to jobs \nSystem Software Engineer (Embedded)\nSunnyvale, CA\n\nApply \nCerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. Our novel wafer-scale architecture provides the AI compute power of dozens of GPUs on a single chip, with the programming simplicity of a single device. This approach allows Cerebras to deliver industry-leading training and inference speeds and empowers machine learning users to effortlessly run large-scale ML applications, without the hassle of managing hundreds of GPUs or TPUs. \n\nCerebras' current customers include top model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras , to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference. \n\nThanks to the groundbreaking wafer-scale architecture, Cerebras Inference offers the fastest Generative AI inference solution in the world, over 10 times faster than GPU-based hyperscale cloud inference services. This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nThe Role \n\nAs part of the Embedded Software team, you will help build the critical software foundation that powers the Cerebras Wafer Scale Engine (WSE)—the world’s largest AI processor. Our team owns a diverse range of embedded and system level components that enable the WSE to operate reliably at scale, including microcontroller firmware, wafer level monitoring logic, system administration services, and the Linux platform and BSP layers that keep the entire system running smoothly. \n\nThis role exists at the intersection of embedded systems, platform engineering, and distributed system enablement. As our technology and deployments continue to scale, we are expanding the team with versatile engineers eager to work across multiple layers of the software stack. You will help build administrative services that connect the WSE’s system software to cluster - level orchestration, collaborate closely "},{"ref":"P18","kind":"page","title":"Senior Mechanical Engineer","date":"2026-06-11T04:13:48.694132+00:00","date_source":null,"source_url":"https://job-boards.greenhouse.io/cerebrassystems/jobs/7522557003","signal_url":null,"signal_json_url":null,"text":"Job Application for Senior Mechanical Engineer at Cerebras Systems \n\nBack to jobs \nSenior Mechanical Engineer\nSunnyvale, CA\n\nApply \nCerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. Our novel wafer-scale architecture provides the AI compute power of dozens of GPUs on a single chip, with the programming simplicity of a single device. This approach allows Cerebras to deliver industry-leading training and inference speeds and empowers machine learning users to effortlessly run large-scale ML applications, without the hassle of managing hundreds of GPUs or TPUs. \n\nCerebras' current customers include top model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras , to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference. \n\nThanks to the groundbreaking wafer-scale architecture, Cerebras Inference offers the fastest Generative AI inference solution in the world, over 10 times faster than GPU-based hyperscale cloud inference services. This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nAbout The Role\n\nAs a Senior Mechanical Engineer at Cerebras, you will lead the design of mechanical systems for our next-generation wafer-scale engine. Your responsibilities will include ensuring compliance with specifications, validating manufacturability, and delivering a high-quality product in a fast-paced environment—tackling some of the most challenging problems in the rapidly evolving AI space.\n\nIn this role, you will develop mechanical infrastructure for Cerebras’ custom hardware system.\n\nRapidly iterate on designs and analysis to inform high level systems trades and steer overall product direction.\n\nProvide comprehensive support for environmental and performance testing on hardware, validating analyses, and ensuring compliance with design criteria.\n\nOwnership of technical deliverables within.\n\nConduct first article inspections, functional analysis, identify and resolve issues.\n\nCollaborate across design"},{"ref":"P19","kind":"page","title":"Design Validation Test - Lead/Principal Engineer","date":"2026-06-11T04:13:48.576139+00:00","date_source":null,"source_url":"https://job-boards.greenhouse.io/cerebrassystems/jobs/7652064003","signal_url":null,"signal_json_url":null,"text":"Job Application for Design Validation Test - Lead/Principal Engineer at Cerebras Systems \n\nBack to jobs \nDesign Validation Test - Lead/Principal Engineer\nSunnyvale, CA\n\nApply \nCerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. Our novel wafer-scale architecture provides the AI compute power of dozens of GPUs on a single chip, with the programming simplicity of a single device. This approach allows Cerebras to deliver industry-leading training and inference speeds and empowers machine learning users to effortlessly run large-scale ML applications, without the hassle of managing hundreds of GPUs or TPUs. \n\nCerebras' current customers include top model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras , to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference. \n\nThanks to the groundbreaking wafer-scale architecture, Cerebras Inference offers the fastest Generative AI inference solution in the world, over 10 times faster than GPU-based hyperscale cloud inference services. This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nRole Summary \n\nWe are seeking a hands‑on DVT Technical Lead (Individual Contributor) to own and drive the Design Validation Test (DVT) process end‑to‑end across complex electrical engineering boards and full systems. You will define validation strategy, build test plans and infrastructure, lead deep debug and root‑cause analysis (RCA), and drive closure through design changes and re‑test. The domain includes difficult power delivery technology, fast high‑speed I/O, and electro‑mechanical systems with thermal, optics, and high‑power constraints. People management is not required (mentoring is a plus).\n\nWhat You’ll Own \n\n1) Board / Subassembly DVT (EE-heavy) \n\nOwn DVT for complex PCBAs and subassemblies from first power‑on through design sign‑off.\n\nPower validation: power‑up/down sequencing, regulator/hotswap behavior, rail margining, DC IR drop, and AC noise/ripple char"},{"ref":"P20","kind":"page","title":"QA Lead (ML Integration and Quality)","date":"2026-06-11T04:13:48.371554+00:00","date_source":null,"source_url":"https://job-boards.greenhouse.io/cerebrassystems/jobs/7647324003","signal_url":null,"signal_json_url":null,"text":"Job Application for QA Lead (ML Integration and Quality) at Cerebras Systems \n\nBack to jobs \nQA Lead (ML Integration and Quality)\nBengaluru, Karnataka, India\n\nApply \nCerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. Our novel wafer-scale architecture provides the AI compute power of dozens of GPUs on a single chip, with the programming simplicity of a single device. This approach allows Cerebras to deliver industry-leading training and inference speeds and empowers machine learning users to effortlessly run large-scale ML applications, without the hassle of managing hundreds of GPUs or TPUs. \n\nCerebras' current customers include top model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras , to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference. \n\nThanks to the groundbreaking wafer-scale architecture, Cerebras Inference offers the fastest Generative AI inference solution in the world, over 10 times faster than GPU-based hyperscale cloud inference services. This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nAbout The Role \n\nAs an ML QA Lead, you ensure quality of Cerebras SW across all supported ML workloads and workflows. You will be part of MIQ (ML Integration and Quality) team that will focus on SW components feature testing, ML training accuracy and performance, pre deployment/production validation, validating customer workloads and workflows.\n\nAs part of this role, you will influence the best testing practice, good debugging methodology, effective cross team communication and advocate for world-class products.\n\nResponsibilities \n\nDrive quality of various software and hardware components of Cerebras solution to ensure accuracy, performance and usability of model trainings.\n\nBring good testing methodology, effective communication and strong debugging skills to the team.\n\nDemand the highest quality from all components within the Cerebras environment.\n\nAbility to automate workflow"},{"ref":"P21","kind":"page","title":"Physical Design Engineer","date":"2026-06-11T04:13:48.366616+00:00","date_source":null,"source_url":"https://job-boards.greenhouse.io/cerebrassystems/jobs/7724730003","signal_url":null,"signal_json_url":null,"text":"page_title \n\nBack to jobs \nPhysical Design Engineer\nBengaluru, Karnataka, India\n\nApply \nCerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. Our novel wafer-scale architecture provides the AI compute power of dozens of GPUs on a single chip, with the programming simplicity of a single device. This approach allows Cerebras to deliver industry-leading training and inference speeds and empowers machine learning users to effortlessly run large-scale ML applications, without the hassle of managing hundreds of GPUs or TPUs. \n\nCerebras' current customers include top model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras , to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference. \n\nThanks to the groundbreaking wafer-scale architecture, Cerebras Inference offers the fastest Generative AI inference solution in the world, over 10 times faster than GPU-based hyperscale cloud inference services. This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nAbout The Role \n\nAs our team grows Cerebras is looking for a world class physical design engineer. We are looking for a strong learner who can learn how we do PD and integration of our wafer scale design.\nAs a member of our tight knit physical design team, you will perform a variety of physical design tasks such as synthesis, place and route, timing and block closure / sign off. You will be involved in all aspects of physical design and implementation. You will work closely with the RTL team and with full-chip integration of these blocks.\n\nSkills and Qualifications \n\n7+ years of physical design/verification experience.\n\nStrong experience in block/subsystem timing closure.\n\nStrong ability to learn and grow with the team.\n\nStrong knowledge of block level and full-chip physical verification methodology.\n\nExpert at optimizing for the best power/performance and area.\n\nExperience with the complete physical design flow. Knowledge of Synopsys tool suite is a plus"},{"ref":"P22","kind":"page","title":"Staff Site Reliability Engineer – Automation and Platform ","date":"2026-06-11T04:13:48.255425+00:00","date_source":null,"source_url":"https://job-boards.greenhouse.io/cerebrassystems/jobs/7487314003","signal_url":null,"signal_json_url":null,"text":"Job Application for Staff Site Reliability Engineer – Automation and Platform at Cerebras Systems \n\nBack to jobs \nStaff Site Reliability Engineer – Automation and Platform \nRemote, California, United States; Sunnyvale, CA; Toronto, Ontario, Canada\n\nApply \nCerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. Our novel wafer-scale architecture provides the AI compute power of dozens of GPUs on a single chip, with the programming simplicity of a single device. This approach allows Cerebras to deliver industry-leading training and inference speeds and empowers machine learning users to effortlessly run large-scale ML applications, without the hassle of managing hundreds of GPUs or TPUs. \n\nCerebras' current customers include top model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras , to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference. \n\nThanks to the groundbreaking wafer-scale architecture, Cerebras Inference offers the fastest Generative AI inference solution in the world, over 10 times faster than GPU-based hyperscale cloud inference services. This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nAbout the Role \n\nWe are building a high-performance SRE function to support one of the world’s fastest-growing AI inference services, powered by the Wafer-Scale Engine (WSE). This team will help deliver world-class, ultra-reliable inference infrastructure for leading model builders such as OpenAI and other frontier labs. \n\nAs a Staff SRE, you will lead the engineering effort to eliminate toil at scale by driving implementation of self-service delivery pipelines, shared observability common tooling. This role starts with ~1 month of hands-on operational immersion to gain deep familiarity with our current stack, production pain points, and high-stakes workflows. \n\nFrom there, your primary focus shifts to architecting and delivering the \"tomorrow\" layer: declarative GitOps-driven CD for model "},{"ref":"P23","kind":"page","title":"Staff Kernel Optimzation Engineer ","date":"2026-06-11T04:13:47.998739+00:00","date_source":null,"source_url":"https://job-boards.greenhouse.io/cerebrassystems/jobs/7620254003","signal_url":null,"signal_json_url":null,"text":"Job Application for Staff Kernel Optimzation Engineer at Cerebras Systems \n\nBack to jobs \nStaff Kernel Optimzation Engineer \nRemote, California, United States\n\nApply \nCerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. Our novel wafer-scale architecture provides the AI compute power of dozens of GPUs on a single chip, with the programming simplicity of a single device. This approach allows Cerebras to deliver industry-leading training and inference speeds and empowers machine learning users to effortlessly run large-scale ML applications, without the hassle of managing hundreds of GPUs or TPUs. \n\nCerebras' current customers include top model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras , to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference. \n\nThanks to the groundbreaking wafer-scale architecture, Cerebras Inference offers the fastest Generative AI inference solution in the world, over 10 times faster than GPU-based hyperscale cloud inference services. This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nAbout The Role \nAs a Kernel Engineer on our team, you will develop high-performance software solutions at the intersection of hardware and software, developing high-performance software for cutting-edge AI and HPC workloads. Your focus will be on implementing, optimizing, and scaling deep learning operations to fully leverage our custom, massively parallel processor architecture.\nYou will be part of a world-class team responsible for the design, performance tuning, and validation of foundational ML and HPC kernels. This includes building a library of parallel and distributed algorithms that maximize compute utilization and push the boundaries of training efficiency for state-of-the-art AI models. Your work will be critical to unlocking the full potential of our hardware and accelerating the pace of AI innovation.\nResponsibilities \n\nDevelop design specifications for new machine "},{"ref":"P24","kind":"page","title":"Senior Technical Program Manager – AI Infrastructure, Site Operations","date":"2026-06-11T04:13:47.901441+00:00","date_source":null,"source_url":"https://job-boards.greenhouse.io/cerebrassystems/jobs/7522548003","signal_url":null,"signal_json_url":null,"text":"Job Application for Senior Technical Program Manager – AI Infrastructure, Site Operations at Cerebras Systems \n\nBack to jobs \nSenior Technical Program Manager – AI Infrastructure, Site Operations\nSunnyvale, CA\n\nApply \nCerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. Our novel wafer-scale architecture provides the AI compute power of dozens of GPUs on a single chip, with the programming simplicity of a single device. This approach allows Cerebras to deliver industry-leading training and inference speeds and empowers machine learning users to effortlessly run large-scale ML applications, without the hassle of managing hundreds of GPUs or TPUs. \n\nCerebras' current customers include top model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras , to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference. \n\nThanks to the groundbreaking wafer-scale architecture, Cerebras Inference offers the fastest Generative AI inference solution in the world, over 10 times faster than GPU-based hyperscale cloud inference services. This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nAbout The Role\n\nThis Sr. TPM role owns site and data center operations programs supporting Cerebras’ AI Cloud and customer deployments. The position sits at Sunnyvale HQ and works closely with Hardware Engineering, Inference Engineering, and Operations leadership to ensure Cerebras systems are reliably deployed, operated, and scaled. \n\nThis is a highly technical, execution-focused TPM role with strong emphasis on operational readiness, cross-functional coordination, and metrics/KPIs.\n\nResponsibilities \n\nOwn end-to-end technical programs for data center and site operations\n\nAct as single-threaded owner across:\n\nHardware & Systems Engineering\n\nAI Cloud Infrastructure & Operations\n\nNetwork & Storage Engineering\n\nFacilities, power, cooling, and colo partners\n\nDrive site readiness for Cerebras Wafer-Scale Engine systems\n\nPartner on "},{"ref":"P25","kind":"page","title":"Software Development Engineer in Test (Cloud) ","date":"2026-06-11T04:13:47.80362+00:00","date_source":null,"source_url":"https://job-boards.greenhouse.io/cerebrassystems/jobs/7730279003","signal_url":null,"signal_json_url":null,"text":"Job Application for Software Development Engineer in Test (Cloud) at Cerebras Systems \n\nBack to jobs \nSoftware Development Engineer in Test (Cloud) \nBengaluru, Karnataka, India\n\nApply \nCerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. Our novel wafer-scale architecture provides the AI compute power of dozens of GPUs on a single chip, with the programming simplicity of a single device. This approach allows Cerebras to deliver industry-leading training and inference speeds and empowers machine learning users to effortlessly run large-scale ML applications, without the hassle of managing hundreds of GPUs or TPUs. \n\nCerebras' current customers include top model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras , to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference. \n\nThanks to the groundbreaking wafer-scale architecture, Cerebras Inference offers the fastest Generative AI inference solution in the world, over 10 times faster than GPU-based hyperscale cloud inference services. This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nAbout The Team\n\nThe Cloud Quality team is responsible for the confidence behind every production release shipped to Cerebras Inference Cloud.\n\nWe work closely with platform, infrastructure, ML systems, and product engineering teams to ensure that rapid iteration never comes at the expense of customer trust. Our environment spans distributed cloud systems, multi-region deployments, APIs, orchestration layers, and hardware-backed inference services.\n\nWe are scaling quickly. The systems are growing in complexity, traffic is increasing rapidly, and release velocity remains high. We need engineers who can build quality systems that scale with the business.\n\nAbout The Role\n\nWe are hiring a Software Development Engineer in Test to own the quality of our weekly cloud releases end to end and to build the test infrastructure that lets the team scale. This is a hands-on "},{"ref":"P26","kind":"page","title":"Senior Cost Accounting Manager","date":"2026-06-11T04:13:47.784569+00:00","date_source":null,"source_url":"https://job-boards.greenhouse.io/cerebrassystems/jobs/7612274003","signal_url":null,"signal_json_url":null,"text":"Job Application for Senior Cost Accounting Manager at Cerebras Systems \n\nBack to jobs \nSenior Cost Accounting Manager\nSunnyvale, CA\n\nApply \nCerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. Our novel wafer-scale architecture provides the AI compute power of dozens of GPUs on a single chip, with the programming simplicity of a single device. This approach allows Cerebras to deliver industry-leading training and inference speeds and empowers machine learning users to effortlessly run large-scale ML applications, without the hassle of managing hundreds of GPUs or TPUs. \n\nCerebras' current customers include top model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras , to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference. \n\nThanks to the groundbreaking wafer-scale architecture, Cerebras Inference offers the fastest Generative AI inference solution in the world, over 10 times faster than GPU-based hyperscale cloud inference services. This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nAbout The Role\n\nThe Senior Cost Accounting Manager will thrive in a fast-paced, dynamic environment supporting both Finance and Operations. This role requires excellent communication skills, strong computational and analytical ability, and the capacity to quickly derive insights from high volume manufacturing and inventory-related transactions. The ideal candidate is proactive, detail-oriented, and comfortable owning end-to-end cost accounting processes. This is a high visibility role working closely with leaders in Supply Chain, Procurement and Finance.\n\nResponsibilities\n\nCost Capitalization & Allocations\n\nAssess, capitalize, and allocate inventory rebates.\n\nEvaluate and allocate wafer manufacturing yield losses.\n\nCapitalize operational costs and manufacturing overhead, ensuring accurate classification for variance analysis.\n\nBook monthly facilities allocations.\n\nAccrue and capitalize freight and tariff"},{"ref":"P27","kind":"page","title":"Senior Hardware Technical Program Manager","date":"2026-06-11T04:13:47.132423+00:00","date_source":null,"source_url":"https://job-boards.greenhouse.io/cerebrassystems/jobs/7675820003","signal_url":null,"signal_json_url":null,"text":"Job Application for Senior Hardware Technical Program Manager at Cerebras Systems \n\nBack to jobs \nSenior Hardware Technical Program Manager\nSunnyvale, CA\n\nApply \nCerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. Our novel wafer-scale architecture provides the AI compute power of dozens of GPUs on a single chip, with the programming simplicity of a single device. This approach allows Cerebras to deliver industry-leading training and inference speeds and empowers machine learning users to effortlessly run large-scale ML applications, without the hassle of managing hundreds of GPUs or TPUs. \n\nCerebras' current customers include top model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras , to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference. \n\nThanks to the groundbreaking wafer-scale architecture, Cerebras Inference offers the fastest Generative AI inference solution in the world, over 10 times faster than GPU-based hyperscale cloud inference services. This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nThe Role\n\nAs a Senior Hardware Technical Program Manager at Cerebras, you will spearhead operational excellence for our high-performance AI compute systems and data centers. You will own the end-to-end hardware schedule for design and engineering improvements, report on engineering issues, and define mitigation strategies. You will own the schedule, implementation, and software integration of hardware changes. You will collaborate closely with electrical and system engineering, manufacturing, supply chain, and system software to drive end-to-end schedule of improvements to our wafer-scale engine supercomputers. Your role will be critical in ensuring seamless translation of product strategy and engineering constraints into the creation and execution of massive supercomputer deployments in the US and abroad.\n\nResponsibilities \n\nOwn end-to-end program schedule for engineering improveme"},{"ref":"P28","kind":"page","title":"Senior Accountant ","date":"2026-06-11T04:13:46.785967+00:00","date_source":null,"source_url":"https://job-boards.greenhouse.io/cerebrassystems/jobs/7748840003","signal_url":null,"signal_json_url":null,"text":"Job Application for Senior Accountant at Cerebras Systems \n\nBack to jobs \nSenior Accountant \nSunnyvale, CA\n\nApply \nCerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. Our novel wafer-scale architecture provides the AI compute power of dozens of GPUs on a single chip, with the programming simplicity of a single device. This approach allows Cerebras to deliver industry-leading training and inference speeds and empowers machine learning users to effortlessly run large-scale ML applications, without the hassle of managing hundreds of GPUs or TPUs. \n\nCerebras' current customers include top model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras , to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference. \n\nThanks to the groundbreaking wafer-scale architecture, Cerebras Inference offers the fastest Generative AI inference solution in the world, over 10 times faster than GPU-based hyperscale cloud inference services. This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nAbout The Role\n\nThe Senior Operations Accountant will be a key contributor to the Finance and Operations teams, reporting to the Senior Cost Accounting Manager. This role is designed for a detail-oriented professional who excels in fast-paced environments and can derive insights from complex manufacturing and inventory data. You will support the end-to-end execution of cost accounting and fixed asset processes.\n\nResponsibilities\n\nCost Capitalization & Inventory Accounting\n\nExecute monthly inventory reconciliations and post all related journal entries.\n\nPerform calculations for inventory rebates, wafer manufacturing yield losses, and monthly facilities allocations.\n\nAccrue and capitalize freight and tariff costs on a monthly basis.\n\nEnsure proper inventory classification across Raw Materials (RM), Work-in-Process (WIP), and Finished Goods (FG).\n\nSupport the coordination of physical inventory counts with Operations and external au"},{"ref":"E1","kind":"event","title":"cerebras/GLM-4.5-Air-REAP-82B-A12B","date":"2025-10-20T15:44:06+00:00","date_source":"source","source_url":"https://huggingface.co/cerebras/GLM-4.5-Air-REAP-82B-A12B","signal_url":"https://onlylabs.fyi/signals/73c7d80f-06d2-42d9-bb0f-fffefb8b778a","signal_json_url":"https://onlylabs.fyi/signals/73c7d80f-06d2-42d9-bb0f-fffefb8b778a/signal.json","text":"model_released · cerebras/GLM-4.5-Air-REAP-82B-A12B · signal_desk=releases · occurred_at=2025-10-20T15:44:06+00:00 · url=https://huggingface.co/cerebras/GLM-4.5-Air-REAP-82B-A12B · hf_downloads=79 · hf_likes=111 · hf_params=81932181504 · pipeline=text-generation · license=mit · raw={\"derived_reason\":\"first-party-finetune\"}"},{"ref":"E2","kind":"event","title":"cerebras/Qwen3-Coder-REAP-25B-A3B","date":"2025-10-20T15:40:03+00:00","date_source":"source","source_url":"https://huggingface.co/cerebras/Qwen3-Coder-REAP-25B-A3B","signal_url":"https://onlylabs.fyi/signals/57d4a7a7-43b8-4605-bb94-cac37e063744","signal_json_url":"https://onlylabs.fyi/signals/57d4a7a7-43b8-4605-bb94-cac37e063744/signal.json","text":"model_released · cerebras/Qwen3-Coder-REAP-25B-A3B · signal_desk=releases · occurred_at=2025-10-20T15:40:03+00:00 · url=https://huggingface.co/cerebras/Qwen3-Coder-REAP-25B-A3B · hf_downloads=508 · hf_likes=83 · hf_params=24867354624 · pipeline=text-generation · license=apache-2.0 · raw={\"derived_reason\":\"first-party-finetune\"}"},{"ref":"E3","kind":"event","title":"cerebras/GLM-4.7-Flash-REAP-23B-A3B","date":"2026-01-23T05:26:34+00:00","date_source":"source","source_url":"https://huggingface.co/cerebras/GLM-4.7-Flash-REAP-23B-A3B","signal_url":"https://onlylabs.fyi/signals/4853c7eb-6324-4e2c-9738-37b91aac9725","signal_json_url":"https://onlylabs.fyi/signals/4853c7eb-6324-4e2c-9738-37b91aac9725/signal.json","text":"model_released · cerebras/GLM-4.7-Flash-REAP-23B-A3B · signal_desk=releases · occurred_at=2026-01-23T05:26:34+00:00 · url=https://huggingface.co/cerebras/GLM-4.7-Flash-REAP-23B-A3B · hf_downloads=392 · hf_likes=76 · hf_params=22996118432 · pipeline=text-generation · license=mit · raw={\"derived_reason\":\"first-party-finetune\"}"},{"ref":"E4","kind":"event","title":"cerebras/Llama3-DocChat-1.0-8B","date":"2024-08-13T21:35:51+00:00","date_source":"source","source_url":"https://huggingface.co/cerebras/Llama3-DocChat-1.0-8B","signal_url":"https://onlylabs.fyi/signals/07054904-4e48-4453-a3ce-816fa17e449f","signal_json_url":"https://onlylabs.fyi/signals/07054904-4e48-4453-a3ce-816fa17e449f/signal.json","text":"model_released · cerebras/Llama3-DocChat-1.0-8B · signal_desk=releases · occurred_at=2024-08-13T21:35:51+00:00 · url=https://huggingface.co/cerebras/Llama3-DocChat-1.0-8B · hf_downloads=12 · hf_likes=69 · pipeline=text-generation · license=other"},{"ref":"E5","kind":"event","title":"cerebras/Kimi-Linear-REAP-35B-A3B-Instruct","date":"2025-11-06T19:37:36+00:00","date_source":"source","source_url":"https://huggingface.co/cerebras/Kimi-Linear-REAP-35B-A3B-Instruct","signal_url":"https://onlylabs.fyi/signals/842740a8-3ed1-4b51-a981-da9d0ccac76d","signal_json_url":"https://onlylabs.fyi/signals/842740a8-3ed1-4b51-a981-da9d0ccac76d/signal.json","text":"model_released · cerebras/Kimi-Linear-REAP-35B-A3B-Instruct · signal_desk=releases · occurred_at=2025-11-06T19:37:36+00:00 · url=https://huggingface.co/cerebras/Kimi-Linear-REAP-35B-A3B-Instruct · hf_downloads=37 · hf_likes=68 · hf_params=35132220360 · pipeline=text-generation · license=mit · raw={\"derived_reason\":\"first-party-finetune\"}"},{"ref":"E6","kind":"event","title":"Applied Machine Learning Research Scientist","date":"2026-06-10T20:57:13+00:00","date_source":"greenhouse.updated_at","source_url":"https://job-boards.greenhouse.io/cerebrassystems/jobs/7655035003","signal_url":"https://onlylabs.fyi/signals/2fcb0767-c8a3-41d1-8716-30806e2c3875","signal_json_url":"https://onlylabs.fyi/signals/2fcb0767-c8a3-41d1-8716-30806e2c3875/signal.json","text":"job_opened · Applied Machine Learning Research Scientist · signal_desk=hiring · occurred_at=2026-06-10T20:57:13+00:00 · url=https://job-boards.greenhouse.io/cerebrassystems/jobs/7655035003 · raw={\"location\":\"Sunnyvale CA or Toronto Canada\",\"ats\":\"greenhouse\"}"},{"ref":"E7","kind":"event","title":"Physical Design Engineer","date":"2026-06-10T15:46:29+00:00","date_source":"greenhouse.updated_at","source_url":"https://job-boards.greenhouse.io/cerebrassystems/jobs/7764007003","signal_url":"https://onlylabs.fyi/signals/9922fd0f-bda3-4e76-aab0-0af69de5dc30","signal_json_url":"https://onlylabs.fyi/signals/9922fd0f-bda3-4e76-aab0-0af69de5dc30/signal.json","text":"job_opened · Physical Design Engineer · signal_desk=hiring · occurred_at=2026-06-10T15:46:29+00:00 · url=https://job-boards.greenhouse.io/cerebrassystems/jobs/7764007003 · raw={\"location\":\"Sunnyvale, CA\",\"ats\":\"greenhouse\"}"},{"ref":"E8","kind":"event","title":"Product Manager, Strategic Verticals ","date":"2026-06-10T13:55:10+00:00","date_source":"greenhouse.updated_at","source_url":"https://job-boards.greenhouse.io/cerebrassystems/jobs/6585289003","signal_url":"https://onlylabs.fyi/signals/137b459d-c025-4948-941f-0a2a2d3d8250","signal_json_url":"https://onlylabs.fyi/signals/137b459d-c025-4948-941f-0a2a2d3d8250/signal.json","text":"job_opened · Product Manager, Strategic Verticals  · signal_desk=hiring · occurred_at=2026-06-10T13:55:10+00:00 · url=https://job-boards.greenhouse.io/cerebrassystems/jobs/6585289003 · raw={\"location\":\"San Francisco, California, United States\",\"ats\":\"greenhouse\"}"},{"ref":"E9","kind":"event","title":"Lead Full Stack Machine Learning Engineer","date":"2026-06-10T07:02:36+00:00","date_source":"greenhouse.updated_at","source_url":"https://job-boards.greenhouse.io/cerebrassystems/jobs/7767933003","signal_url":"https://onlylabs.fyi/signals/e418a3cc-748f-4b77-af56-cb287f138ea0","signal_json_url":"https://onlylabs.fyi/signals/e418a3cc-748f-4b77-af56-cb287f138ea0/signal.json","text":"job_opened · Lead Full Stack Machine Learning Engineer · signal_desk=hiring · occurred_at=2026-06-10T07:02:36+00:00 · url=https://job-boards.greenhouse.io/cerebrassystems/jobs/7767933003 · raw={\"location\":\"Bengaluru, Karnataka, India\",\"ats\":\"greenhouse\"}"},{"ref":"E10","kind":"event","title":"Network Engineer ","date":"2026-06-09T04:55:57+00:00","date_source":"greenhouse.updated_at","source_url":"https://job-boards.greenhouse.io/cerebrassystems/jobs/7762739003","signal_url":"https://onlylabs.fyi/signals/6694a82f-c1b3-4c24-8f15-6e2881bbb4cb","signal_json_url":"https://onlylabs.fyi/signals/6694a82f-c1b3-4c24-8f15-6e2881bbb4cb/signal.json","text":"job_opened · Network Engineer  · signal_desk=hiring · occurred_at=2026-06-09T04:55:57+00:00 · url=https://job-boards.greenhouse.io/cerebrassystems/jobs/7762739003 · raw={\"location\":\"Sunnyvale, CA; Toronto, Ontario, Canada\",\"ats\":\"greenhouse\"}"},{"ref":"E11","kind":"event","title":"Senior / Staff Technical Program Manager - Datacenter Capacity Delivery (E2E) ","date":"2026-06-09T01:22:29+00:00","date_source":"greenhouse.updated_at","source_url":"https://job-boards.greenhouse.io/cerebrassystems/jobs/7762063003","signal_url":"https://onlylabs.fyi/signals/63fc3796-439b-430c-b5ac-d7b851610e36","signal_json_url":"https://onlylabs.fyi/signals/63fc3796-439b-430c-b5ac-d7b851610e36/signal.json","text":"job_opened · Senior / Staff Technical Program Manager - Datacenter Capacity Delivery (E2E)  · signal_desk=hiring · occurred_at=2026-06-09T01:22:29+00:00 · url=https://job-boards.greenhouse.io/cerebrassystems/jobs/7762063003 · raw={\"location\":\"Europe; Remote, California, United States; Sunnyvale, CA; Toronto, Ontario, Canada\",\"ats\":\"greenhouse\"}"},{"ref":"E12","kind":"event","title":"Senior Front End Design Engineer (Microarchitecture)","date":"2026-06-08T19:12:47+00:00","date_source":"greenhouse.updated_at","source_url":"https://job-boards.greenhouse.io/cerebrassystems/jobs/7763907003","signal_url":"https://onlylabs.fyi/signals/e3e04f01-7cfc-49c4-936d-69578dd8e3fb","signal_json_url":"https://onlylabs.fyi/signals/e3e04f01-7cfc-49c4-936d-69578dd8e3fb/signal.json","text":"job_opened · Senior Front End Design Engineer (Microarchitecture) · signal_desk=hiring · occurred_at=2026-06-08T19:12:47+00:00 · url=https://job-boards.greenhouse.io/cerebrassystems/jobs/7763907003 · raw={\"location\":\"Sunnyvale, CA\",\"ats\":\"greenhouse\"}"},{"ref":"E13","kind":"event","title":"Design Verification Engineer","date":"2026-06-08T19:09:23+00:00","date_source":"greenhouse.updated_at","source_url":"https://job-boards.greenhouse.io/cerebrassystems/jobs/7763894003","signal_url":"https://onlylabs.fyi/signals/5bd8c375-4d24-4bf7-b2fc-d80f93e472d2","signal_json_url":"https://onlylabs.fyi/signals/5bd8c375-4d24-4bf7-b2fc-d80f93e472d2/signal.json","text":"job_opened · Design Verification Engineer · signal_desk=hiring · occurred_at=2026-06-08T19:09:23+00:00 · url=https://job-boards.greenhouse.io/cerebrassystems/jobs/7763894003 · raw={\"location\":\"Bengaluru, Karnataka, India\",\"ats\":\"greenhouse\"}"},{"ref":"E14","kind":"event","title":"Prognostics & Health Monitoring Engineer ","date":"2026-06-05T19:30:41+00:00","date_source":"greenhouse.updated_at","source_url":"https://job-boards.greenhouse.io/cerebrassystems/jobs/7720309003","signal_url":"https://onlylabs.fyi/signals/795ed749-d4fb-49c0-bf3f-259ee6561143","signal_json_url":"https://onlylabs.fyi/signals/795ed749-d4fb-49c0-bf3f-259ee6561143/signal.json","text":"job_opened · Prognostics & Health Monitoring Engineer  · signal_desk=hiring · occurred_at=2026-06-05T19:30:41+00:00 · url=https://job-boards.greenhouse.io/cerebrassystems/jobs/7720309003 · raw={\"location\":\"Sunnyvale, CA\",\"ats\":\"greenhouse\"}"},{"ref":"E15","kind":"event","title":"3D Physical Design Engineer","date":"2026-06-04T20:14:31+00:00","date_source":"greenhouse.updated_at","source_url":"https://job-boards.greenhouse.io/cerebrassystems/jobs/6538655003","signal_url":"https://onlylabs.fyi/signals/3c204a4f-f780-49a2-b959-860d40823bea","signal_json_url":"https://onlylabs.fyi/signals/3c204a4f-f780-49a2-b959-860d40823bea/signal.json","text":"job_opened · 3D Physical Design Engineer · signal_desk=hiring · occurred_at=2026-06-04T20:14:31+00:00 · url=https://job-boards.greenhouse.io/cerebrassystems/jobs/6538655003 · raw={\"location\":\"Sunnyvale, CA\",\"ats\":\"greenhouse\"}"},{"ref":"E16","kind":"event","title":"Design Verification Engineer","date":"2026-06-04T18:24:18+00:00","date_source":"greenhouse.updated_at","source_url":"https://job-boards.greenhouse.io/cerebrassystems/jobs/7763846003","signal_url":"https://onlylabs.fyi/signals/bcc464f9-7c76-4e91-b37e-64d2f81b0776","signal_json_url":"https://onlylabs.fyi/signals/bcc464f9-7c76-4e91-b37e-64d2f81b0776/signal.json","text":"job_opened · Design Verification Engineer · signal_desk=hiring · occurred_at=2026-06-04T18:24:18+00:00 · url=https://job-boards.greenhouse.io/cerebrassystems/jobs/7763846003 · raw={\"location\":\"Sunnyvale, CA\",\"ats\":\"greenhouse\"}"},{"ref":"E17","kind":"event","title":"Sr. Staff/Staff Design Verification Engineer","date":"2026-06-04T16:45:23+00:00","date_source":"greenhouse.updated_at","source_url":"https://job-boards.greenhouse.io/cerebrassystems/jobs/7763735003","signal_url":"https://onlylabs.fyi/signals/ce6f9f4c-662a-43a3-ae62-984ab8c89be0","signal_json_url":"https://onlylabs.fyi/signals/ce6f9f4c-662a-43a3-ae62-984ab8c89be0/signal.json","text":"job_opened · Sr. Staff/Staff Design Verification Engineer · signal_desk=hiring · occurred_at=2026-06-04T16:45:23+00:00 · url=https://job-boards.greenhouse.io/cerebrassystems/jobs/7763735003 · raw={\"location\":\"Sunnyvale, CA\",\"ats\":\"greenhouse\"}"},{"ref":"E18","kind":"event","title":"Business Operations Lead, Datacenters","date":"2026-06-04T16:39:35+00:00","date_source":"greenhouse.updated_at","source_url":"https://job-boards.greenhouse.io/cerebrassystems/jobs/7763752003","signal_url":"https://onlylabs.fyi/signals/c583b8f4-6f00-42a3-893f-827fce52e2d7","signal_json_url":"https://onlylabs.fyi/signals/c583b8f4-6f00-42a3-893f-827fce52e2d7/signal.json","text":"job_opened · Business Operations Lead, Datacenters · signal_desk=hiring · occurred_at=2026-06-04T16:39:35+00:00 · url=https://job-boards.greenhouse.io/cerebrassystems/jobs/7763752003 · raw={\"location\":\"Sunnyvale, CA\",\"ats\":\"greenhouse\"}"},{"ref":"E19","kind":"event","title":"ASIC Architect","date":"2026-06-04T15:55:00+00:00","date_source":"greenhouse.updated_at","source_url":"https://job-boards.greenhouse.io/cerebrassystems/jobs/7753254003","signal_url":"https://onlylabs.fyi/signals/8ee66e56-6412-4944-ad9c-51224149d46e","signal_json_url":"https://onlylabs.fyi/signals/8ee66e56-6412-4944-ad9c-51224149d46e/signal.json","text":"job_opened · ASIC Architect · signal_desk=hiring · occurred_at=2026-06-04T15:55:00+00:00 · url=https://job-boards.greenhouse.io/cerebrassystems/jobs/7753254003 · raw={\"location\":\"Sunnyvale, CA\",\"ats\":\"greenhouse\"}"},{"ref":"E20","kind":"event","title":"Senior Quality Engineer","date":"2026-06-04T00:00:52+00:00","date_source":"greenhouse.updated_at","source_url":"https://job-boards.greenhouse.io/cerebrassystems/jobs/7720337003","signal_url":"https://onlylabs.fyi/signals/6884d1e7-fc13-4ad9-a309-92b82565cdb6","signal_json_url":"https://onlylabs.fyi/signals/6884d1e7-fc13-4ad9-a309-92b82565cdb6/signal.json","text":"job_opened · Senior Quality Engineer · signal_desk=hiring · occurred_at=2026-06-04T00:00:52+00:00 · url=https://job-boards.greenhouse.io/cerebrassystems/jobs/7720337003 · raw={\"location\":\"Sunnyvale, CA\",\"ats\":\"greenhouse\"}"},{"ref":"E21","kind":"event","title":"Director / Senior Director, Critical Facility Operations ","date":"2026-06-03T01:46:45+00:00","date_source":"greenhouse.updated_at","source_url":"https://job-boards.greenhouse.io/cerebrassystems/jobs/7762028003","signal_url":"https://onlylabs.fyi/signals/3fe67e58-74ae-438f-a14d-8f938a2911e2","signal_json_url":"https://onlylabs.fyi/signals/3fe67e58-74ae-438f-a14d-8f938a2911e2/signal.json","text":"job_opened · Director / Senior Director, Critical Facility Operations  · signal_desk=hiring · occurred_at=2026-06-03T01:46:45+00:00 · url=https://job-boards.greenhouse.io/cerebrassystems/jobs/7762028003 · raw={\"location\":\"Sunnyvale, CA\",\"ats\":\"greenhouse\"}"},{"ref":"E22","kind":"event","title":"Infrastructure Hardware Technical Program Manager (Server and Network Systems)","date":"2026-06-03T01:46:11+00:00","date_source":"greenhouse.updated_at","source_url":"https://job-boards.greenhouse.io/cerebrassystems/jobs/7636808003","signal_url":"https://onlylabs.fyi/signals/ada8eed8-decf-48fe-9cda-c9f88db8fa65","signal_json_url":"https://onlylabs.fyi/signals/ada8eed8-decf-48fe-9cda-c9f88db8fa65/signal.json","text":"job_opened · Infrastructure Hardware Technical Program Manager (Server and Network Systems) · signal_desk=hiring · occurred_at=2026-06-03T01:46:11+00:00 · url=https://job-boards.greenhouse.io/cerebrassystems/jobs/7636808003 · raw={\"location\":\"Sunnyvale CA or Toronto Canada\",\"ats\":\"greenhouse\"}"},{"ref":"E23","kind":"event","title":" LLM Inference Performance & Evals Engineer","date":"2026-06-03T01:46:11+00:00","date_source":"greenhouse.updated_at","source_url":"https://job-boards.greenhouse.io/cerebrassystems/jobs/6658665003","signal_url":"https://onlylabs.fyi/signals/f4663a60-53e0-4cb5-81bf-88b61d1465e3","signal_json_url":"https://onlylabs.fyi/signals/f4663a60-53e0-4cb5-81bf-88b61d1465e3/signal.json","text":"job_opened ·  LLM Inference Performance & Evals Engineer · signal_desk=hiring · occurred_at=2026-06-03T01:46:11+00:00 · url=https://job-boards.greenhouse.io/cerebrassystems/jobs/6658665003 · raw={\"location\":\"Toronto, Ontario, Canada\",\"ats\":\"greenhouse\"}"},{"ref":"E24","kind":"event","title":"Head of Data Center 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of IT · signal_desk=hiring · occurred_at=2026-06-03T01:46:11+00:00 · url=https://job-boards.greenhouse.io/cerebrassystems/jobs/7677635003 · raw={\"location\":\"Sunnyvale, CA\",\"ats\":\"greenhouse\"}"},{"ref":"E26","kind":"event","title":"Design Validation Test - Lead/Principal Engineer","date":"2026-06-03T01:46:11+00:00","date_source":"greenhouse.updated_at","source_url":"https://job-boards.greenhouse.io/cerebrassystems/jobs/7652064003","signal_url":"https://onlylabs.fyi/signals/bc91da1b-d657-476c-a479-d4eceab5b3a4","signal_json_url":"https://onlylabs.fyi/signals/bc91da1b-d657-476c-a479-d4eceab5b3a4/signal.json","text":"job_opened · Design Validation Test - Lead/Principal Engineer · signal_desk=hiring · occurred_at=2026-06-03T01:46:11+00:00 · url=https://job-boards.greenhouse.io/cerebrassystems/jobs/7652064003 · raw={\"location\":\"Sunnyvale, CA\",\"ats\":\"greenhouse\"}"},{"ref":"E27","kind":"event","title":"Director of Costing 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Kernel Engineer · signal_desk=hiring · occurred_at=2026-06-03T01:46:11+00:00 · url=https://job-boards.greenhouse.io/cerebrassystems/jobs/7486714003 · raw={\"location\":\"Bengaluru, Karnataka, India\",\"ats\":\"greenhouse\"}"},{"ref":"E30","kind":"event","title":"ML Software Tool Development Engineer","date":"2026-06-03T01:46:11+00:00","date_source":"greenhouse.updated_at","source_url":"https://job-boards.greenhouse.io/cerebrassystems/jobs/7634141003","signal_url":"https://onlylabs.fyi/signals/93102016-02a1-4e75-a2bc-e46f3d982340","signal_json_url":"https://onlylabs.fyi/signals/93102016-02a1-4e75-a2bc-e46f3d982340/signal.json","text":"job_opened · ML Software Tool Development Engineer · signal_desk=hiring · occurred_at=2026-06-03T01:46:11+00:00 · url=https://job-boards.greenhouse.io/cerebrassystems/jobs/7634141003 · raw={\"location\":\"Sunnyvale CA or Toronto Canada\",\"ats\":\"greenhouse\"}"},{"ref":"E31","kind":"event","title":"Senior GL 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Engineer · signal_desk=hiring · occurred_at=2026-06-03T01:46:11+00:00 · url=https://job-boards.greenhouse.io/cerebrassystems/jobs/7618093003 · raw={\"location\":\"Sunnyvale CA or Toronto Canada\",\"ats\":\"greenhouse\"}"},{"ref":"E33","kind":"event","title":"Senior ML Systems Engineer","date":"2026-06-03T01:46:11+00:00","date_source":"greenhouse.updated_at","source_url":"https://job-boards.greenhouse.io/cerebrassystems/jobs/7622330003","signal_url":"https://onlylabs.fyi/signals/c3105564-e232-40a8-ab75-53b7cd1607f5","signal_json_url":"https://onlylabs.fyi/signals/c3105564-e232-40a8-ab75-53b7cd1607f5/signal.json","text":"job_opened · Senior ML Systems Engineer · signal_desk=hiring · occurred_at=2026-06-03T01:46:11+00:00 · url=https://job-boards.greenhouse.io/cerebrassystems/jobs/7622330003 · raw={\"location\":\"Sunnyvale CA or Toronto Canada\",\"ats\":\"greenhouse\"}"},{"ref":"E34","kind":"event","title":"Senior/Staff Engineer : Post Silicon- Bring 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