Senior Machine Learning Engineer

About this role

ABOUT THE ROLE

A growing AI and Data Science team at a healthcare-focused company is looking for a Senior Machine Learning Engineer to take ownership of complex, enterprise-scale ML initiatives. This is a W2 contract role for work-authorized candidates (no visa sponsorship available). You'll work in a fast-paced environment building production-grade ML solutions that directly impact patient outcomes and healthcare operations — with a strong emphasis on compliance, reliability, and end-to-end ownership.

Ideal candidates bring 8+ years of professional ML engineering experience and a mandatory background in the healthcare industry, including hands-on experience with HIPAA-compliant systems and sensitive patient data.

WHAT YOU'LL DO

- Own the full ML lifecycle: data ingestion, feature engineering, model training, evaluation, deployment, monitoring, retraining, and maintenance.

- Design and build scalable, production-ready ML systems with high availability, performance, and reliability.

- Develop and maintain MLOps pipelines — including CI/CD, model registry, feature stores, automated deployment, monitoring, and rollback strategies.

- Monitor production models for drift (model, data, accuracy degradation) and overall system health.

- Build and integrate REST APIs to connect ML services into enterprise cloud applications.

- Optimize models for latency, scalability, reliability, and operational cost.

- Provide technical leadership on AI/ML initiatives across the organization.

- Collaborate with Data Engineers, Software Engineers, Product Managers, Clinical teams, and business stakeholders.

- Ensure strict compliance with HIPAA, PHI, PII, and enterprise security standards throughout all ML workflows.

WHAT WE'RE LOOKING FOR

Required — Dealbreakers:

- 8+ years of professional software engineering and machine learning experience.

- Healthcare domain experience is mandatory — including HIPAA compliance and handling of sensitive patient data (PHI/PII).

- Demonstrated ownership of end-to-end ML lifecycle from data preparation through deployment, monitoring, and retraining.

- Experience designing and operating production-grade ML systems at scale.

- Hands-on MLOps: CI/CD pipelines, model registry, feature stores, automated deployment, monitoring, and rollback.

Required Technical Skills:

- Languages: Python, SQL

- Platforms: Databricks (production), Apache Spark (distributed computing), MLflow, Feature Store, Model Registry

- Cloud: Azure, AWS, and/or GCP for ML workloads

- Infrastructure: Docker, Kubernetes, REST APIs, Git, CI/CD pipelines

- Strong debugging and performance-tuning skills; excellent stakeholder communication.

Nice to Have:

- LLMs in production, prompt engineering, RAG, and/or GenAI applications

- Scala

- Azure ML, SageMaker, or Vertex AI

- Distributed ML architecture design

- HIPAA-compliant AI solution design experience

COMPENSATION & DETAILS

- Rate: $70–75/hr on W2 (equivalent to ~$145,600–$156,000 annualized)

- Type: W2 Contract

- Visa sponsorship: Not available — open to all work-authorized candidates

LOCATION

Primary location: San Francisco, CA. Additional locations considered include Los Angeles, CA and New York City, NY. Remote-friendly role.

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