Senior Machine Learning Engineer

About the role

This is a Senior Machine Learning Engineer role embedded within a growing AI and Data Science team at a healthcare-focused data and analytics company. You’ll take end-to-end ownership of enterprise-scale ML solutions — from raw data through to production — playing a critical part in delivering compliant, high-impact AI capabilities in a regulated healthcare environment.

Responsibilities

• Design, develop, deploy, and maintain enterprise-scale machine learning solutions from the ground up.
• Build end-to-end ML pipelines covering data ingestion, feature engineering, model training, evaluation, deployment, monitoring, and retraining.
• Develop and maintain MLOps pipelines including CI/CD, 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.
• Collaborate cross-functionally with Data Engineers, Software Engineers, Product Managers, and Clinical teams.
• Provide technical leadership on AI/ML initiatives and ensure compliance with HIPAA, PHI, and PII standards.

Requirements

• 8+ years of professional software engineering and machine learning experience.
• Strong healthcare industry background — this is a firm requirement.
• Deep expertise across the full ML lifecycle: preprocessing, feature engineering, model development, calibration, deployment, monitoring, and maintenance.
• Hands-on MLOps experience with strong Python and SQL skills.
• Proficiency with distributed computing (Apache Spark) and Databricks in production environments.
• Experience with at least one major cloud platform (Azure, AWS, or GCP).
• Familiarity with MLflow, Feature Stores, Model Registries, Docker, and Git.
• Experience building and integrating REST APIs; strong debugging and performance-tuning skills.
• Working knowledge of HIPAA compliance requirements when handling sensitive healthcare data.

Nice to have

• LLMs in production, RAG/prompt engineering, GenAI
• Kubernetes, Scala, or managed ML platforms (Azure ML, SageMaker, Vertex AI)

Pay

Hourly contract rate of $70–$75/hr on W2, equivalent to approximately $145,600–$156,000 annually. This is a contract (W2) engagement.

Location

Based in Palo Alto, CA. Work arrangement details to be confirmed with the hiring team.