Interwell Health

Interwell Health

Machine Learning Engineer

Remote, United States

Sponsorship not specifiedDetected 91 days ago
PythonScalaSQLDatabricksAWSGCPAzureCI/CDAPI DevelopmentMachine LearningSparkData AnalysisLLMsMLOpsStatisticsComplianceHIPAACommunicationProblem SolvingPublic Speaking

About the role

  • This Machine Learning Engineer is comfortable working with both traditional tabular machine learning models and modern AI techniques, including prompt engineering and LLM‑based capabilities.
  • We value our differences and learn from each other.
  • Our team members come in all shapes, colors, and sizes.

Responsibilities

  • Collaborate closely with engineers, product managers, clinicians, and cross‑functional partners to build new ML products and enhance existing systems.
  • Lead the design and implementation of MLOps frameworks, including pipeline development, CI/CD integration, drift detection, retraining workflows, and rollback strategies.
  • Utilize contemporary software engineering practices to implement scalable, secure, and maintainable AI/ML systems.
  • Develop and customize API integrations to enable seamless connectivity between cloud‑based systems and ML services.
  • 3+ years of MLOps experience building production pipelines (CI/CD, model registry, feature store), implementing monitoring & drift detection, and automating retraining.
  • If there is a better way, we will create it.

Requirements

  • Bachelor's degree in Computer Science, Data Analytics, Software/Computer Engineering, Computational Statistics, Mathematics, or a related discipline.
  • 3+ years of end‑to‑end ML development in production (data prep, feature engineering, modeling, calibration, deployment, monitoring, maintenance).
  • 2+ years working with distributed compute and cloud ML environments (e.g., Spark/Databricks on Azure/AWS/GCP) and modern data ecosystems (data lakes, DBMS).
  • Track record of ownership and problem solving-driving measurable impact and quality under ambiguity and evolving requirements.
  • Proven understanding of tradeoffs in latency, cost, performance, and compliance.
  • 1+ years of Databricks experience + some experience in infrastructure/networking
  • 1+ years designing compliant ML platforms (e.g., HIPAA, SOC 2) and working with PHI/PII governance, access controls, and auditability.

Nice to have

  • 3+ years of Python for production ML (testing, packaging, type hints, linting) and SQL for analytical and production workloads

Benefits

  • In this role, you will be flexible, eager to learn new skills, and willing to contribute wherever the team needs support.
  • Develop and deliver end‑to‑end machine learning solutions, including defining technical requirements, architecting scalable systems, and implementing monitoring, logging, and maintenance workflows.
  • Monitor model performance in production, identify issues, propose remediation steps, and ensure strong test coverage and system reliability.

Company info

  • We are on a mission to help people and we know the work we do changes their lives.
  • So, if our mission speaks to you, join us!
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This listing is sourced directly from Interwell Health's careers page and normalized into a canonical job model.