VNS Health, New York
Senior ML Engineer
(Dec'22 - Present)
- Designs and implements scalable and reliable machine learning (ML) systems used to develop, test, and deploy machine learning models.
- Leverages technologies and platforms to support reproducible feature engineering and optimized machine learning model deployment at scale.
- Creates robust monitoring solutions to understand model performance and manage model life cycles via a centralized model registry.
- Partners with data scientists and IT data engineers to understand business priorities, frame machine learning problems, and architect machine learning solutions.
- Ensures data quality throughout all stages of acquisition and processing, including data sourcing/collection, ground truth generation, normalization, and transformation.
- Identifies gaps and evaluates relevant tools and cloud computing technologies as needed to improve machine learning processes and build effective solutions.
Technology Stack: Python, Airflow, Snowflake, Amazon AWS, SQL, Docker.
Technology Stack: Python, Airflow, Snowflake, Amazon AWS, SQL, Docker.