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
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Design, develop, deploy, and maintain enterprise-scale machine learning solutions from the ground up.
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Build end-to-end ML pipelines covering data ingestion, feature engineering, model training, evaluation, deployment, monitoring, and retraining.
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Develop and maintain MLOps pipelines including CI/CD, model registry, feature stores, automated deployment, and rollback strategies.
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Monitor production models for drift, accuracy degradation, and overall system health.
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Develop REST APIs and integrate ML services into enterprise cloud applications.
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Optimize models for latency, scalability, reliability, and cost.
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Collaborate cross-functionally with Data Engineers, Software Engineers, Product Managers, and Clinical teams.
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Provide technical leadership on AI/ML initiatives and ensure compliance with HIPAA, PHI, and PII standards.
What We're Looking For
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8+ years of professional software engineering and machine learning experience.
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Strong healthcare industry background — this is a firm requirement.
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Deep expertise across the full ML lifecycle: preprocessing, feature engineering, model development, calibration, deployment, monitoring, and maintenance.
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Hands-on MLOps experience with strong Python and SQL skills.
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Proficiency with distributed computing (Apache Spark) and Databricks in production environments.
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Experience with at least one major cloud platform (Azure, AWS, or GCP).
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Familiarity with MLflow, Feature Stores, Model Registries, Docker, and Git.
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Experience building and integrating REST APIs; strong debugging and performance-tuning skills.
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Working knowledge of HIPAA compliance requirements when handling sensitive healthcare data.
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Nice to have: LLMs in production, RAG/prompt engineering, GenAI, Kubernetes, Scala, or managed ML platforms (Azure ML, SageMaker, Vertex AI).
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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.
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