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.