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Bayesian HealthBayesian HealthUnited States

Staff Machine Learning Engineer

Owns end-to-end ML lifecycle from prototyping clinical prediction models to productionizing and deploying them using production-grade Python/SQL. Requires PhD +3yrs or Master's +5yrs experience with MLOps tools like SageMaker/MLFlow.

Salary not listed
RemoteML Engineering

About the role

Responsibilities

  • Model Prototyping: Develop and tune innovative, new ML models and labeler systems based on deep understanding of clinical use cases and state-of-the-art ML methods.
  • Productionizing: The same models that you develop with production-grade python.
  • Deploying: Identify strategies for improving our production ML-based systems, and write, debug, and deploying production-grade Python code to implement those strategies.
  • MLOps: Build infrastructure that enables ML model development and deployment in production systems.

Minimum Qualifications

  • Ph.D. in a relevant field plus 3+ years relevant experience, or a relevant Master’s degree and 5+ years experience shipping ML based software products.
  • Experience owning your ML models from prototyping to production.
  • Experience writing production-grade Python and SQL code to implement and evaluate ML models in production systems.
  • Experience using MLOps tools such as SageMaker and MLFlow.

Preferred Qualifications

  • Experience going 0-1 and shipping high impact AI/ML products.
  • Experience building solutions within healthcare and/or familiarity working with messy health data.
  • Experience working with enterprise customers, and the agility and responsiveness they require.
  • Comfortable interpreting / leveraging state-of-the-art peer-reviewed methods or tools in designing your approach.

Skills

Machine LearningPythonSQLSageMakerMLflowMLOpsAWS

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