{"schema_version":"onlylabs.public_signal.v1","title":"LG AI Research (EXAONE) Job: (인재풀) MLOps Engineer","description":"LG AI Research (EXAONE) job signal with public source context, captured evidence pages, related signals, and category-scoped analysis context.","url":"https://onlylabs.fyi/signals/340ccaa8-48c4-494d-9814-2951d2080c81","json_url":"https://onlylabs.fyi/signals/340ccaa8-48c4-494d-9814-2951d2080c81/signal.json","generated_at":"2026-06-11T03:17:32.916908+00:00","org":{"slug":"lg-ai","name":"LG AI Research (EXAONE)","category":"neolab","category_label":"Neolab","dossier_url":"https://onlylabs.fyi/labs/lg-ai","dossier_json_url":"https://onlylabs.fyi/labs/lg-ai/dossier.json"},"related_urls":{"signal":"https://onlylabs.fyi/signals/340ccaa8-48c4-494d-9814-2951d2080c81","signal_json":"https://onlylabs.fyi/signals/340ccaa8-48c4-494d-9814-2951d2080c81/signal.json","source":"https://job-boards.greenhouse.io/lgairesearch/jobs/4012564005","lab_dossier":"https://onlylabs.fyi/labs/lg-ai","lab_dossier_json":"https://onlylabs.fyi/labs/lg-ai/dossier.json","analysis":"https://onlylabs.fyi/analysis/lg-ai","analysis_json":"https://onlylabs.fyi/analysis/lg-ai/analysis.json","analysis_evidence_json":"https://onlylabs.fyi/analysis/lg-ai/evidence.json","category":"https://onlylabs.fyi/neolabs","category_json":"https://onlylabs.fyi/neolabs.json","category_feed":"https://onlylabs.fyi/neolabs/feed.xml","category_signals_json":"https://onlylabs.fyi/signals.json?category=neolab","topic":"https://onlylabs.fyi/topics/hiring","topic_signals_json":"https://onlylabs.fyi/topics/hiring/signals.json?category=neolab","topic_feed":"https://onlylabs.fyi/topics/hiring/feed.xml?category=neolab","data_business":null},"answer_pack":{"answer":"LG AI Research (EXAONE) opened (인재풀) MLOps Engineer (Gangseo-gu, Seoul, South Korea). This hiring signal is demand evidence for teams, locations, and technical bets being staffed. High-signal details: location Gangseo-gu, Seoul, South Korea · Routine job posting. onlylabs links this event to 1 captured evidence page and 6 related job signals.","signal_desk":"hiring","source_context":{"source_url":"https://job-boards.greenhouse.io/lgairesearch/jobs/4012564005","source_host":"job-boards.greenhouse.io","occurred_at":"2026-04-29T14:36:04+00:00","first_seen_at":"2026-06-05T20:58:46.903695+00:00","date_source":"source","context":"Gangseo-gu, Seoul, South Korea"},"context_markers":[{"label":"Lab","value":"LG AI Research (EXAONE)","source":"signal"},{"label":"Signal desk","value":"hiring","source":"signal"},{"label":"Source host","value":"job-boards.greenhouse.io","source":"source"},{"label":"Location","value":"Gangseo-gu, Seoul, South Korea","source":"signal"},{"label":"ATS","value":"greenhouse","source":"source"},{"label":"Notability","value":"Routine job posting","source":"signal"},{"label":"Watch term","value":"Infrastructure","source":"evidence"},{"label":"Watch term","value":"Agents and tool use","source":"evidence"}],"evidence_coverage":{"target_pages":1,"captured_pages":1,"readable_pages":1,"capture_methods":["plain"],"missing_page_urls":[],"failed_page_urls":[],"blocked_page_urls":[],"page_urls":["https://job-boards.greenhouse.io/lgairesearch/jobs/4012564005"],"related_signals":6,"has_source_url":true,"latest_page_fetched_at":"2026-06-11T03:17:32.916908+00:00"},"data_business":{"matches":false,"lanes":[],"matched_terms":[],"score":null,"reason":null},"agent_handoff":{"signal_json":"https://onlylabs.fyi/signals/340ccaa8-48c4-494d-9814-2951d2080c81/signal.json","dossier_json":"https://onlylabs.fyi/labs/lg-ai/dossier.json","analysis_json":"https://onlylabs.fyi/analysis/lg-ai/analysis.json","analysis_evidence_json":"https://onlylabs.fyi/analysis/lg-ai/evidence.json","topic_signals_json":"https://onlylabs.fyi/topics/hiring/signals.json?category=neolab","topic_feed":"https://onlylabs.fyi/topics/hiring/feed.xml?category=neolab","category_signals_json":"https://onlylabs.fyi/signals.json?category=neolab","data_radar_json":null,"opportunities_json":null},"analysis_playbook":{"objective":"Turn open roles into leading indicators for teams, locations, infrastructure needs, eval work, data demand, and commercialization buildout.","evidence_focus":["role title","team or function","location","job description","data, eval, infra, safety, product, and GTM terms"],"extraction_questions":["Which teams are hiring repeatedly?","Which locations or hubs are becoming more important?","Which roles imply data, evaluation, infrastructure, or platform spend?","Which labs have hiring signals without a fresh standing analysis?"],"signal_questions":["What demand signal does this role create for teams, locations, infrastructure, evals, or data workflows?","Which teams are hiring repeatedly?","Which locations or hubs are becoming more important?","Do the 6 related job signals show a repeated pattern?"],"output_fields":["org","team","location","role_theme","evidence_url"],"data_business_relevance":"Data-business lane extraction is scoped to frontier labs; for this category, keep conclusions tied to category-specific strategy, source evidence, and follow-up questions.","required_sources":[{"label":"signal_json","url":"https://onlylabs.fyi/signals/340ccaa8-48c4-494d-9814-2951d2080c81/signal.json","required":true},{"label":"source","url":"https://job-boards.greenhouse.io/lgairesearch/jobs/4012564005","required":true},{"label":"dossier_json","url":"https://onlylabs.fyi/labs/lg-ai/dossier.json","required":true},{"label":"analysis_evidence_json","url":"https://onlylabs.fyi/analysis/lg-ai/evidence.json","required":true},{"label":"topic_signals_json","url":"https://onlylabs.fyi/topics/hiring/signals.json?category=neolab","required":false},{"label":"data_radar_json","url":null,"required":false}],"expected_output":["one-paragraph source-grounded interpretation","category-specific implication","confidence and missing evidence","recommended next source to inspect"],"prompt_seed":"Using only the linked onlylabs JSON, captured source context, and cited evidence, analyze LG AI Research (EXAONE)'s job signal \"(인재풀) MLOps Engineer\" for neolab strategy."},"semantic_triples":[{"subject":"LG AI Research (EXAONE)","predicate":"opened","object":"role (인재풀) MLOps Engineer","text":"LG AI Research (EXAONE) opened role (인재풀) MLOps Engineer."},{"subject":"(인재풀) MLOps Engineer","predicate":"is classified as","object":"job signal","text":"(인재풀) MLOps Engineer is classified as job signal."},{"subject":"(인재풀) MLOps Engineer","predicate":"belongs to","object":"hiring desk","text":"(인재풀) MLOps Engineer belongs to hiring desk."},{"subject":"(인재풀) MLOps Engineer","predicate":"has context","object":"Gangseo-gu, Seoul, South Korea","text":"(인재풀) MLOps Engineer has context Gangseo-gu, Seoul, South Korea."},{"subject":"(인재풀) MLOps Engineer","predicate":"has evidence coverage","object":"1 captured evidence page","text":"(인재풀) MLOps Engineer has evidence coverage 1 captured evidence page."},{"subject":"(인재풀) MLOps Engineer","predicate":"has captured page count","object":"1","text":"(인재풀) MLOps Engineer has captured page count 1."},{"subject":"(인재풀) MLOps Engineer","predicate":"has readable page count","object":"1","text":"(인재풀) MLOps Engineer has readable page count 1."},{"subject":"(인재풀) MLOps Engineer","predicate":"has related signal count","object":"6","text":"(인재풀) MLOps Engineer has related signal count 6."},{"subject":"(인재풀) MLOps Engineer","predicate":"has analysis playbook objective","object":"Turn open roles into leading indicators for teams, locations, infrastructure needs, eval work, data demand, and commercialization buildout.","text":"(인재풀) MLOps Engineer has analysis playbook objective Turn open roles into leading indicators for teams, locations, infrastructure needs, eval work, data demand, and commercialization buildout.."},{"subject":"(인재풀) MLOps Engineer","predicate":"has source host","object":"job-boards.greenhouse.io","text":"(인재풀) MLOps Engineer has source host job-boards.greenhouse.io."},{"subject":"(인재풀) MLOps Engineer","predicate":"has lab","object":"LG AI Research (EXAONE)","text":"(인재풀) MLOps Engineer has lab LG AI Research (EXAONE)."},{"subject":"(인재풀) MLOps Engineer","predicate":"has signal desk","object":"hiring","text":"(인재풀) MLOps Engineer has signal desk hiring."},{"subject":"(인재풀) MLOps Engineer","predicate":"has source host","object":"job-boards.greenhouse.io","text":"(인재풀) MLOps Engineer has source host job-boards.greenhouse.io."},{"subject":"(인재풀) MLOps Engineer","predicate":"has location","object":"Gangseo-gu, Seoul, South Korea","text":"(인재풀) MLOps Engineer has location Gangseo-gu, Seoul, South Korea."},{"subject":"(인재풀) MLOps Engineer","predicate":"has ats","object":"greenhouse","text":"(인재풀) MLOps Engineer has ats greenhouse."},{"subject":"(인재풀) MLOps Engineer","predicate":"has notability","object":"Routine job posting","text":"(인재풀) MLOps Engineer has notability Routine job posting."},{"subject":"(인재풀) MLOps Engineer","predicate":"has watch term","object":"Infrastructure","text":"(인재풀) MLOps Engineer has watch term Infrastructure."},{"subject":"(인재풀) MLOps Engineer","predicate":"has watch term","object":"Agents and tool use","text":"(인재풀) MLOps Engineer has watch term Agents and tool use."}]},"intelligence":{"signal_desk":"hiring","answer":"LG AI Research (EXAONE) opened (인재풀) MLOps Engineer (Gangseo-gu, Seoul, South Korea). This hiring signal is demand evidence for teams, locations, and technical bets being staffed. High-signal details: location Gangseo-gu, Seoul, South Korea · Routine job posting. onlylabs links this event to 1 captured evidence page and 6 related job signals.","semantic_triples":[{"subject":"LG AI Research (EXAONE)","predicate":"opened","object":"role (인재풀) MLOps Engineer","text":"LG AI Research (EXAONE) opened role (인재풀) MLOps Engineer."},{"subject":"(인재풀) MLOps Engineer","predicate":"is classified as","object":"job signal","text":"(인재풀) MLOps Engineer is classified as job signal."},{"subject":"(인재풀) MLOps Engineer","predicate":"belongs to","object":"hiring desk","text":"(인재풀) MLOps Engineer belongs to hiring desk."},{"subject":"(인재풀) MLOps Engineer","predicate":"has context","object":"Gangseo-gu, Seoul, South Korea","text":"(인재풀) MLOps Engineer has context Gangseo-gu, Seoul, South Korea."},{"subject":"(인재풀) MLOps Engineer","predicate":"has evidence coverage","object":"1 captured evidence page","text":"(인재풀) MLOps Engineer has evidence coverage 1 captured evidence page."}]},"signal":{"id":"340ccaa8-48c4-494d-9814-2951d2080c81","url":"https://onlylabs.fyi/signals/340ccaa8-48c4-494d-9814-2951d2080c81","json_url":"https://onlylabs.fyi/signals/340ccaa8-48c4-494d-9814-2951d2080c81/signal.json","source_url":"https://job-boards.greenhouse.io/lgairesearch/jobs/4012564005","title":"(인재풀) MLOps Engineer","summary":"LG AI Research (EXAONE) opened a hiring signal. onlylabs watches roles as demand indicators for teams, locations, and technical bets.","context":"Gangseo-gu, Seoul, South Korea","kind":{"key":"job_opened","label":"Job"},"org":{"slug":"lg-ai","name":"LG AI Research (EXAONE)","category":"neolab"},"occurred_at":"2026-04-29T14:36:04+00:00","first_seen_at":"2026-06-05T20:58:46.903695+00:00","date_source":"source","evidence_coverage":{"target_pages":1,"captured_pages":1,"readable_pages":1,"capture_methods":["plain"],"missing_page_urls":[],"failed_page_urls":[],"blocked_page_urls":[],"page_urls":["https://job-boards.greenhouse.io/lgairesearch/jobs/4012564005"]},"facets":{"location":"Gangseo-gu, Seoul, South Korea","ats":"greenhouse"},"traction":{"github_stars":null,"hn_points":null,"hn_comments":null,"hn_story_id":null,"hf_downloads":null,"hf_likes":null},"data_radar":null},"primary_evidence_page":{"url":"https://job-boards.greenhouse.io/lgairesearch/jobs/4012564005","final_url":"https://job-boards.greenhouse.io/lgairesearch/jobs/4012564005","title":"(인재풀) MLOps Engineer","http_status":200,"content_type":"text/html; charset=utf-8","capture_method":"plain","fetched_at":"2026-06-11T03:17:32.916908+00:00","bytes":42563,"raw_path":"d58631f5377c96b8e22f24396b69a7a84677ff7195339f2fda2c6b1900fc07fd.html","content_hash":"09f8f61f67164f34ab7b6a722dba55d1394a16ec136d41d4e7c448fa4d598a56","excerpt_chars":1200,"truncated":true,"excerpt":"LG AI Research의 (인재풀) MLOps Engineer 직무 입사 지원서 채용 정보로 돌아가기 (인재풀) MLOps Engineer Gangseo-gu, Seoul, South Korea Apply 팀 소개 Platform&Infra팀은 AI 모델의 개발부터 서비스 운영을 위한 배포에 이르기까지 AI 모델의 수명 주기를 최적화하고, 효율적으로 관리하기 위한 MLOps 파이프라인을 구축합니다. 또한 AI 서비스의 안정적인 운영 지원을 위한 보안성 강화, 인프라 관리 및 자원 최적화 업무를 수행합니다. 수행 업무 AI 모델 학습/추론을 위한 플랫폼을 설계하고 개발합니다. 학습, 추론, 모니터링이 포함된 Container-native Workflow를 개발하고 운영합니다. Kubernetes 환경에서 Micro-service Architecture 기반의 서비스를 개발하고 운영합니다. 다양한 도메인의 ML/DL 모델을 최적화하고, 서비스 환경에 맞게 배포 및 운영합니다. 지원자격 GCP, AWS, Azure 같은 Public Cloud에서 AI 관련 개발 경험이 있으신 분 Kubernetes를 구축하고, Docker 및 Kubernetes 환경에서 서비스를 배포/운영해본 경험이 있으신 분 모델의 성능 개선을 위해 모니터링 시스템을 구축하고, 이를 바탕으로 성능을 개선해본 경험이 있으신 분 ML/DL에 대한 기본적인 이해가 있고, 이를 활용하여 시스템을 설계하거나 문제를 해결해본 경험이 있으신 분 우대자격 CI/CD 도구(Helm, Kustomize, ArgoCD 등)를 활용한 개발 및 운영을 해봤으면 좋아요. Infrastructure-as-a-Code (Terraform 등) 기반의 인프라 관리를 해봤으면 좋아요. AI Serving Framework (Triton, TensorRT LLM, vLLM, SGLang 등)를 사용해봤으면 좋아요. Workflow 관리 도구(Airflow, Kubeflow, Argo Workflows 등)를 활용해봤으면 좋아요. On-Premise 환경에서 서비스 개발 및 운영을 해봤으면 좋아요. 머신러닝 모델을 경량화하거나 서빙을 최적화해봤으면 좋아요. 복잡한 기술 개념을 명확하고 쉽게 설명하는 커뮤니케이션을 해봤으면 좋아요. 전형 절차 서류심사 → 코딩테스트 → 1차 직무 인터뷰(온라인) → 2차 직무 인터뷰(온라인) → LG AI Fit Check(온라인) →..."},"evidence_pages":[{"url":"https://job-boards.greenhouse.io/lgairesearch/jobs/4012564005","final_url":"https://job-boards.greenhouse.io/lgairesearch/jobs/4012564005","title":"(인재풀) MLOps Engineer","http_status":200,"content_type":"text/html; charset=utf-8","capture_method":"plain","fetched_at":"2026-06-11T03:17:32.916908+00:00","bytes":42563,"raw_path":"d58631f5377c96b8e22f24396b69a7a84677ff7195339f2fda2c6b1900fc07fd.html","content_hash":"09f8f61f67164f34ab7b6a722dba55d1394a16ec136d41d4e7c448fa4d598a56","excerpt_chars":1200,"truncated":true,"excerpt":"LG AI Research의 (인재풀) MLOps Engineer 직무 입사 지원서 채용 정보로 돌아가기 (인재풀) MLOps Engineer Gangseo-gu, Seoul, South Korea Apply 팀 소개 Platform&Infra팀은 AI 모델의 개발부터 서비스 운영을 위한 배포에 이르기까지 AI 모델의 수명 주기를 최적화하고, 효율적으로 관리하기 위한 MLOps 파이프라인을 구축합니다. 또한 AI 서비스의 안정적인 운영 지원을 위한 보안성 강화, 인프라 관리 및 자원 최적화 업무를 수행합니다. 수행 업무 AI 모델 학습/추론을 위한 플랫폼을 설계하고 개발합니다. 학습, 추론, 모니터링이 포함된 Container-native Workflow를 개발하고 운영합니다. Kubernetes 환경에서 Micro-service Architecture 기반의 서비스를 개발하고 운영합니다. 다양한 도메인의 ML/DL 모델을 최적화하고, 서비스 환경에 맞게 배포 및 운영합니다. 지원자격 GCP, AWS, Azure 같은 Public Cloud에서 AI 관련 개발 경험이 있으신 분 Kubernetes를 구축하고, Docker 및 Kubernetes 환경에서 서비스를 배포/운영해본 경험이 있으신 분 모델의 성능 개선을 위해 모니터링 시스템을 구축하고, 이를 바탕으로 성능을 개선해본 경험이 있으신 분 ML/DL에 대한 기본적인 이해가 있고, 이를 활용하여 시스템을 설계하거나 문제를 해결해본 경험이 있으신 분 우대자격 CI/CD 도구(Helm, Kustomize, ArgoCD 등)를 활용한 개발 및 운영을 해봤으면 좋아요. Infrastructure-as-a-Code (Terraform 등) 기반의 인프라 관리를 해봤으면 좋아요. AI Serving Framework (Triton, TensorRT LLM, vLLM, SGLang 등)를 사용해봤으면 좋아요. Workflow 관리 도구(Airflow, Kubeflow, Argo Workflows 등)를 활용해봤으면 좋아요. On-Premise 환경에서 서비스 개발 및 운영을 해봤으면 좋아요. 머신러닝 모델을 경량화하거나 서빙을 최적화해봤으면 좋아요. 복잡한 기술 개념을 명확하고 쉽게 설명하는 커뮤니케이션을 해봤으면 좋아요. 전형 절차 서류심사 → 코딩테스트 → 1차 직무 인터뷰(온라인) → 2차 직무 인터뷰(온라인) → LG AI Fit Check(온라인) →..."}],"related_signals":[{"id":"1ad9621c-3161-4f7e-86b7-c36a60f48656","url":"https://onlylabs.fyi/signals/1ad9621c-3161-4f7e-86b7-c36a60f48656","source_url":"https://job-boards.greenhouse.io/lgairesearch/jobs/4646683005","title":"(인재풀) Research Scientist Internship - Computer Vision","context":"Seoul, Seoul, South Korea","kind":{"key":"job_opened","label":"Job"},"org":{"slug":"lg-ai","name":"LG AI Research (EXAONE)","category":"neolab"},"occurred_at":"2026-06-11T01:57:22+00:00","first_seen_at":"2026-06-11T07:01:00.214165+00:00","date_source":"greenhouse.updated_at"},{"id":"c1e1ac22-1054-42d1-a8d2-a7f1ddc6b7b3","url":"https://onlylabs.fyi/signals/c1e1ac22-1054-42d1-a8d2-a7f1ddc6b7b3","source_url":"https://job-boards.greenhouse.io/lgairesearch/jobs/4653405005","title":"Information Security Internship","context":"Gangseo-gu, Seoul, South Korea","kind":{"key":"job_opened","label":"Job"},"org":{"slug":"lg-ai","name":"LG AI Research (EXAONE)","category":"neolab"},"occurred_at":"2026-06-10T13:20:06+00:00","first_seen_at":"2026-06-11T07:01:00.214165+00:00","date_source":"greenhouse.updated_at"},{"id":"60d340ff-51d1-4595-a4b4-d8d3c7658b7a","url":"https://onlylabs.fyi/signals/60d340ff-51d1-4595-a4b4-d8d3c7658b7a","source_url":"https://job-boards.greenhouse.io/lgairesearch/jobs/4699587005","title":"AI R&D Strategy & Planning Specialist (AI R&D 전략기획 담당자)","context":"Gangseo-gu, Seoul, South Korea","kind":{"key":"job_opened","label":"Job"},"org":{"slug":"lg-ai","name":"LG AI Research (EXAONE)","category":"neolab"},"occurred_at":"2026-06-05T04:51:55+00:00","first_seen_at":"2026-06-05T20:58:46.903695+00:00","date_source":"greenhouse.updated_at"},{"id":"2aba9634-e570-445c-9efb-e7ca2b392599","url":"https://onlylabs.fyi/signals/2aba9634-e570-445c-9efb-e7ca2b392599","source_url":"https://job-boards.greenhouse.io/lgairesearch/jobs/4700115005","title":"법무 행정업무 지원(계약직)","context":"Gangseo-gu, Seoul, South Korea","kind":{"key":"job_opened","label":"Job"},"org":{"slug":"lg-ai","name":"LG AI Research (EXAONE)","category":"neolab"},"occurred_at":"2026-05-28T07:52:32+00:00","first_seen_at":"2026-06-05T20:58:46.903695+00:00","date_source":"greenhouse.updated_at"},{"id":"16c990ae-e2e1-4e3a-bf33-7da1d33920d2","url":"https://onlylabs.fyi/signals/16c990ae-e2e1-4e3a-bf33-7da1d33920d2","source_url":"https://job-boards.greenhouse.io/lgairesearch/jobs/4179929005","title":"UX/UI Designer Internship","context":"Gangseo-gu, Seoul, South Korea","kind":{"key":"job_opened","label":"Job"},"org":{"slug":"lg-ai","name":"LG AI Research (EXAONE)","category":"neolab"},"occurred_at":"2026-05-08T04:57:45+00:00","first_seen_at":"2026-06-05T20:58:46.903695+00:00","date_source":"greenhouse.updated_at"},{"id":"75dac0a6-dd95-4d2b-a898-20e5f2044930","url":"https://onlylabs.fyi/signals/75dac0a6-dd95-4d2b-a898-20e5f2044930","source_url":"https://job-boards.greenhouse.io/lgairesearch/jobs/4693142005","title":"Robotics Evaluation & Benchmark Internship ","context":"Gangseo-gu, Seoul, South Korea","kind":{"key":"job_opened","label":"Job"},"org":{"slug":"lg-ai","name":"LG AI Research (EXAONE)","category":"neolab"},"occurred_at":"2026-05-07T09:02:44+00:00","first_seen_at":"2026-06-05T20:58:46.903695+00:00","date_source":"greenhouse.updated_at"}]}