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. WHAT YOU'LL DO - 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. WHAT WE'RE LOOKING FOR - 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). - US work authorization required; visa sponsorship is not available. COMPENSATION & BENEFITS Hourly contract rate of $70–$75/hr on W2, equivalent to approximately $145,600–$156,000 annually. This is a contract (W2) engagement. Visa sponsorship is not available. LOCATION Based in Palo Alto, CA. Work arrangement details to be confirmed with the hiring team.