10 ml ops engineer jobs at 8 companies in Napa, CA
6d
Save
Mark Applied
Hide
6d
Staff Cloud/ML Ops Engineer
San Francisco, California, United States
$287k-$485k/yrOnsiteFull Time
Ivo: AI-powered contract review and intelligence platform for legal teams.
7+ years experience; production Kubernetes expertise; IaC (Pulumi/Terraform); multi-cluster/multi-region design; CI/CD (GitHub); security controls, observability, and partnership with SRE/ML teams.
Kubernetes, AWS, GCP, Azure, Pulumi, Terraform, GitHub CI/CD, Microsoft Word
San Francisco or Chicago or Scottsdale or New York
$118k-$203k/yrHybridFull Time
Early Warning Services: Operates payment and risk solutions for the financial industry.
5+ YOEBachelor's in CS/Engineering; 5+ years in Data Science/ML/Ops; Python; AWS; Docker/Kubernetes; MLflow/Kubeflow; real-time model deployment; strong data/compute systems knowledge.
BlackLineNASDAQ: BL: Provides cloud-based financial close and accounting automation software.
2+ YOE2+ years in Python/Java/Scala, experience building PySpark ETL, ML/LLM production pipelines, cloud (GCP/AWS/Azure), ML frameworks, orchestration, containerization, and observability.
BlackLineNASDAQ: BL: Provides cloud-based financial close and accounting automation software.
Extensive experience building and operating ML/AI production systems, designing scalable data pipelines, distributed training, model deployment, CI/CD, observability, and cloud infrastructure.
Co-Op, LS AI, ML Scientist for Protein Engineering
San Francisco, California, United States
OnsiteInternship, Temporary
Lila Sciences: Develops an AI platform for autonomous scientific research and discovery.
PhD student in a quantitative field with ML and computational biology research experience; strong Python programming and experience with PyTorch or JAX; ability to work with biological datasets and communicate results.
8+ YOEPhD (8+ yrs) or MS (10+ yrs) in a relevant technical field; 8+ years designing, building, and deploying ML/DL/Gen-AI models; hands-on experience with production ML/LLM ops, scalable systems, and leading technical teams.