Machine Learning Platform Engineer

You may choose to display a cookie banner on the external site. You must specify the message in the cookie banner and may add a link to a relevant policy. If you are unfamiliar with these requirements, please seek the advice of legal counsel. )Site : The Brigham and Women's Hospital, Inc.Mass General Brigham relies on a wide range of professionals, including doctors, nurses, business people, tech experts, researchers, and systems analysts to advance our mission. As a not-for-profit, we support patient care, research, teaching, and community service, striving to provide exceptional care. We believe that high-performing teams drive groundbreaking medical discoveries and invite all applicants to join us and experience what it means to be part of Mass General Brigham.We are looking for a motivated, responsible, and self-directed Machine Learning Platform Engineer to maintain and enhance our cloud-scale ML platform. In this critical role, you will lead the integration of ML models with clinical workflows—particularly within Epic EHR systems—and implement best practices in ML Ops to ensure reliability, scalability, and reproducibility.

While experience with ML Ops / DevOps practices is beneficial, direct machine learning experience is not required. We prioritize enthusiasm, ownership, and eagerness to learn.

Principal Duties and Responsibilities :

• Maintain and continuously develop our ML platform, ensuring reliable operation and scalability.
• Integrate ML models seamlessly into clinical workflows, with a particular focus on integration within Epic EHR systems.
• Implement and manage ML Ops best practices, including model deployment, monitoring, version control, and reproducibility.
• Facilitate the deployment, scaling, and management of dockerized pipeline containers
• Lead the development and improvement of user interfaces (ReactJS)
• Expand the ML platform’s capabilities, including support for Large Language Models (LLMs).
• Perform SQL-based data queries for efficient ingestion, extraction, and preparation of datasets.
• Generate and maintain high-quality datasets tailored to ML research and clinical studies.
• Oversee quality assurance processes, documentation standards, and best practices for the ML platform infrastructure.
• Job Summary
• Summary

Responsible for implementing methods to improve data reliability and quality. They combine raw information from different sources to create consistent and machine-readable formats and they develop and test architectures that enable data extraction and transformation for predictive or prescriptive modeling.

No

Essential Functions

Bachelor's Degree Computer Science required or Bachelor's Degree Related Field of Study required

Yes

Licenses and Credentials

Experience

Data warehousing development in large reporting environment(s) 2-3 years required and Experience with developing data pipelines using on Snowflake features ( Snowpipe, SnowSQL, Snow Sight, Data Streams ) required and Hands-on development experience with ETL / ELT tools, such as dbt, Fivetran, or Informatica required and Experience working in Agile software development environment required

Knowledge, Skills and Abilities

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