Senior Machine Learning Engineer

Clera

  • Palo Alto, California
  • 4 days ago

    Highlights

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

    Numbers & Facts

    LocationPalo Alto, California
    Websitehttps://www.getclera.com/

    Description

    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.