Dana-Farber Cancer Institute is looking to solve the problem of building reusable and scalable AI/ML tools and pipelines to support operations, research, and clinical practice.
Requirements
- Familiarity with Python.
- R, Databricks, and/or Snowflake experience preferred.
- Experience with one of the following: MLOPS and ML engineering; GenAI and agentic AI; AL/ML and data science; data engineering and pipelines.
- 1 year of work experience in machine learning and AI required.
- Experience within a clinical or research environment preferred.
- Bachelor’s degree in a related field (Computer Science, Data Science, Engineering) required.
- Master’s degree preferred.
Responsibilities
- Contribute to the development, deployment, and monitoring of AI solutions, supporting scalable and efficient practices to ensure reliable telemetry tracking, model performance monitoring, and cross-platform efficiency.
- Assist in implementing and maintaining data and machine learning solutions, helping to manage models throughout their lifecycle to ensure they are well-organized, auditable, and maintain high accuracy.
- Support the creation and maintenance of CI/CD pipelines for machine learning models in cloud environments, including workflows for batch, online, streaming, and edge training/inference.
- Elicit functional requirements from end users and data science teams, utilizing methods such as user interviews, mockups, wireframes, end-to-end testing, prototypes, GUI designs, and use cases.
- Provide updates on assigned tasks and project progress to multiple groups include the AIOS team, client-facing leads, project sponsors, business owners, and internal stakeholders.
- Work effectively as part of a team, contributing to shared goals and supporting the success of projects and initiatives.
- Assist in implementing and maintaining data engineering and pipelines.
Other
- Excellent communication and effective problem-solving skills.
- Track record in serving a variety of diverse customers and projects.
- Ability to work independently, prioritize, and adapt to meet the evolving needs of the Institute.
- Bachelor’s degree in a related field (Computer Science, Data Science, Engineering) required.
- Master’s degree preferred.
