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.
About the job
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 Learning, Python, SQL, SageMaker, MLflow, MLOps, AWS
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