Mlops Engineer

Stanford Health Care

Stanford, California, USA
Base: $79.21 - $104.97 ph; bonus/equity: not speci...
Not specified
Kubernetes
Terraform
Langgraph
Stanford Health Care is seeking a Senior AI Platform & MLOps Engineer to design and implement scalable infrastructure for AI systems in healthcare. The ideal candidate should have extensive experience in MLOps, DevOps, and cloud technologies, and will play a key role in integrating AI into clinical and operational workflows

Job Summary

  • We are seeking a high-caliber Senior AI Platform & ML Ops Engineer to architect the "layered" infrastructure required for autonomous, agentic systems within Stanford Healthcare.
  • You won't just manage servers; you will build the robust, full-stack "factory" where multi-agent frameworks interact with healthcare APIs, ensuring every autonomous action is governed by strict ML Ops observability and safety guardrails.
  • The MLOPs Engineer will play an integral role incorporating Artificial Intelligence (AI) within Stanford Health Care, impacting patient care, medical research, and operational services.

Matching Summary

Match Score: 85

Stanford Health Care is seeking a Senior AI Platform & MLOps Engineer to design and implement scalable infrastructure for AI systems in healthcare. The ideal candidate should have extensive experience in MLOps, DevOps, and cloud technologies, and will play a key role in integrating AI into clinical and operational workflows.

Salary

Base: $79.21 - $104.97 per hour; Bonus/Equity: Not specified; Benefits: Not specified

Skills & Requirements

Must-have

  • Kubernetes
  • Terraform
  • LangGraph
  • CrewAI
  • LangSmith
  • Arize
  • Python RAG pipelines

Nice-to-have

  • legacy of hope and innovation
  • Master Chef of AI ecosystem
  • crispy coding skills
  • rich architectural depth

Key Requirements

  • Three (3) or more years of directly related experience
  • Bachelor’s or higher degree in Computer Science, Engineering or related field
  • Proven experience as an MLOps Engineer
  • Strong knowledge of cloud platforms (AWS, Azure, Google Cloud)
  • Proficiency in containerization (Docker, Kubernetes)
  • Experience with CI/CD tools (GitLab CI/CD, Github Actions, CircleCI)
  • Solid programming skills (Python, Rust, Go)

Work Rights

Not specified

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