MLOps engineers evaluated on ML pipelines, Kubernetes rollouts, and production monitoring — not DevOps buzzwords.
6 matching full-time / mid-level+ listings
Opt-in Ganloss profiles — contact via recruiter talent pool.
Ingénieur IA / MLOps · GenAI, LLM & pipelines prod
10801 · Hybrid
AI engineer · LLM, MLOps & data
United States · Hybrid or remote
AI engineer · LLM, MLOps & data
United States · Hybrid or remote
AI engineer · LLM, MLOps & data
United States · Hybrid or remote
AI engineer · LLM, MLOps & data
United States · Hybrid or remote
Senior AI / ML · architecture & delivery
United States · Hybrid or remote
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ServiceNow MLOps engineer for model CI/CD and GPU serving — Bellevue / Seattle hybrid enterprise AI platform.
Adobe Sensei ML engineer for document intelligence and creative assist features — hybrid San Francisco with production PyTorch pipelines.
MLOps engineer in Austin — enterprise model CI/CD and GPU scheduling. Active hiring near MLOps World Austin and mlops austin community events.
RAG pipeline jobs building ingestion, chunking, rerank, and eval loops for developer copilots — full-time remote US for rag pipeline jobs and rag developer jobs.
Teams hire Hugging Face engineer profiles for hub integrations, fine-tuning pipelines, and enterprise support — remote US full-time aligned with hire hugging face engineer searches.
Enterprise teams hire machine learning engineer talent through forward-deployed staff — model deployment on Snowflake ML, Cortex, and secure data pipelines in Chicago and remote US.
Generic résumés do not prove production ability. Ganloss evaluates mlops engineers on ML CI/CD pipelines, feature stores, and monitored models in production — not keyword-stuffed skill lists.
Filter by stack, review GitHub, papers, or technical cases, then contact profiles with demonstrated level in the United States. $36/month — no hire commission.
Agencies charge 15–25% of annual salary and often recycle the same LinkedIn profiles. Ganloss combines a niche AI job board, tech talent pool, and project-based matching — hire faster with fewer mismatches.
Publish in about five minutes with Google for Jobs indexing and reach active candidates in the US AI market.