Senior Machine Learning Engineer

Department: Engineering

Location: Palo Alto

Employment Type: FullTime

About the Role

This is a senior individual contributor role on a growing AI and Data Science team, focused on building and owning production-grade machine learning solutions in the healthcare space. You'll operate across the full ML lifecycle — from data preparation through to deployment and ongoing monitoring — with direct impact on clinical and operational outcomes.

What You'll Do

• Design, develop, deploy, and maintain enterprise-scale machine learning solutions end-to-end.

• Build ML pipelines covering data ingestion, feature engineering, model training, evaluation, deployment, monitoring, and retraining.

• Develop and maintain MLOps infrastructure including CI/CD pipelines, model registry, feature stores, automated deployment, and rollback strategies.

• Monitor production models for drift, accuracy degradation, and overall system health.

• Develop REST APIs and integrate ML services into enterprise cloud applications.

• Optimize models for latency, scalability, reliability, and cost.

• Provide technical leadership on AI/ML initiatives across engineering, product, and clinical stakeholders.

• Ensure all solutions comply with HIPAA, PHI/PII handling, and enterprise security standards.

What We're Looking For

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

• Strong, mandatory background in the healthcare industry, including working with sensitive health data under HIPAA and related compliance frameworks.

• Hands-on expertise across the full ML lifecycle: preprocessing, feature engineering, model development, calibration, deployment, and maintenance.

• Proficiency in Python and SQL; strong debugging and performance-tuning skills.

• Experience with distributed computing (Apache Spark) and Databricks in production environments.

• Familiarity with MLflow, feature stores, model registries, and CI/CD tooling for ML.

• Cloud platform experience across Azure, AWS, and/or GCP; comfort with Docker and Git; Kubernetes a plus.

• Experience with LLMs in production, RAG/prompt engineering, or GenAI tooling (e.g. Azure ML, SageMaker, Vertex AI) is a plus.

• Strong communication skills and an ownership mindset in cross-functional environments.

• Must be authorized to work in the US; visa sponsorship is not available.

Compensation & Benefits

This is a W2 contract role with a pay rate of $70–75/hour (equivalent to approximately $145,600–$156,000 annualized). Visa sponsorship is not available; all work-authorized candidates are welcome to apply.

Location

Based in Palo Alto, CA.