Member of Technical Staff, AI Training Infrastructure

Job Application for Member of Technical Staff, AI Training Infrastructure at Fireworks AI

Member of Technical Staff, AI Training Infrastructure San Mateo, CA

About Us:

At Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.

The Role:

As a Training Infrastructure Engineer, you'll design, build, and optimize the infrastructure that powers our large-scale model training operations. Your work will be essential to developing high-performance AI training infrastructure. You'll collaborate with AI researchers and engineers to create robust training pipelines, optimize distributed training workloads, and ensure reliable model development.

Key Responsibilities:

Design and implement scalable infrastructure for large-scale model training workloads

Develop and maintain distributed training pipelines for LLMs and multimodal models

Optimize training performance across multiple GPUs, nodes, and data centers

Implement monitoring, logging, and debugging tools for training operations

Architect and maintain data storage solutions for large-scale training datasets

Automate infrastructure provisioning, scaling, and orchestration for model training

Collaborate with researchers to implement and optimize training methodologies

Analyze and improve efficiency, scalability, and cost-effectiveness of training systems

Troubleshoot complex performance issues in distributed training environments

Minimum Qualifications:

Bachelor's degree in Computer Science, Computer Engineering, or related field, or equivalent practical experience

3+ years of experience with distributed systems and ML infrastructure

Experience with PyTorch

Proficiency in cloud platforms (AWS, GCP, Azure)

Experience with containerization, orchestration (Kubernetes, Docker)

Knowledge of distributed training techniques (data parallelism, model parallelism, FSDP)

Preferred Qualifications:

Master's or PhD in Computer Science or related field

Experience training large language models or multimodal AI systems

Experience with ML workflow orchestration tools

Background in optimizing high-performance distributed computing systems

Familiarity with ML DevOps practices

Contributions to open-source ML infrastructure or related projects

Total compensation for this role also includes meaningful equity in a fast-growing startup, along with a competitive salary and comprehensive benefits package. Base salary is determined by a range of factors including individual qualifications, experience, skills, interview performance, market data, and work location. The listed salary range is intended as a guideline and may be adjusted.

Base Pay Range (Plus Equity) $175,000 - $220,000 USD

Why Fireworks AI?

Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.

Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.

Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.

Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.

Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.

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