Senior ML Platform Engineer: GenAI & MLOps

Spring Health; San Francisco (CA); Hybrid; USD 170,000 - 230,000; Full time

Benefits offered by this job

Health benefits

401(k) match

Parental leave

Professional development reimbursement

Noom/Wellhub programs

Job summary

Spring Health is seeking a Senior Machine Learning Engineer to help build and scale a centralized AI platform that powers care capabilities. The role is hybrid in San Francisco, requiring 2-3 days in the office weekly at 44 Montgomery, with relocation flexibility within 90 days and occasional travel for team on-sites.

The ideal candidate has 4-6 years of Python experience with GenAI/ML libraries, experience with Kubernetes, AWS, and Azure, and a track record of architecting enterprise solutions

Qualifications

• Degree in Computer Science, Data Science, or a related field with a focus on AI/ML.
• 4-6 years of Python development experience with GenAI and ML libraries.
• Experience maintaining and configuring engineering tools, including deployment in a Kubernetes stack.
• Experience driving adoption of generalized platforms with focus on internal Developer Experience (DX).

Responsibilities

• Collaborate to build and scale the AI platform, tooling, and best practices for rapid GenAI deployment.
• Monitor uptime and ensure high availability of AI/ML tools and platform features.
• Lead refactoring initatives to enforce centralized coding standards for platform services.
• Partner with ML teams to modernize MLOps practices and accelerate cross-team adoption.

Skills

Python

GenAI

ML libraries

Kubernetes

DX improvements

Education

Degree in CS/Data Science or related

Tools

Kubernetes

AWS

Azure

LangChain

Pydantic

Scikit-Learn

Job description

Spring Health is seeking a Senior Machine Learning Engineer to help build and scale a centralized AI platform that powers care capabilities. The role is hybrid in San Francisco, requiring 2-3 days in the office weekly at 44 Montgomery, with relocation flexibility within 90 days and occasional travel for team on-sites.

The ideal candidate has 4-6 years of Python experience with GenAI/ML libraries, experience with Kubernetes, AWS, and Azure, and a track record of architecting enterprise solutions