onsite
Machine Learning Engineer - University of California - San Francisco
ML Engineer
Lead the design, implementation, and maintenance of robust data pipelines and ML infrastructure to deploy and monitor AI tools for UCSF research, collaborating across technical teams and delivering customized solutions.
About the role
Key Responsibilities
- Design, build, and maintain scalable data pipelines and ML infrastructure to support research projects.
- Deploy and monitor machine learning and generative AI models, ensuring high availability and performance.
- Collaborate with UCSF technical teams to translate research needs into technical solutions.
- Provide project consultation, grant support, and budget estimations for AI initiatives.
- Document processes, maintain version control, and ensure reproducibility of ML workflows.
Requirements
- Proficiency in Python and experience with ML frameworks (e.g., TensorFlow, PyTorch).
- Strong background in data engineering, SQL, and containerization (Docker).
- Experience building and maintaining production ML pipelines.
- Excellent communication skills and ability to work cross‑functionally.
- Familiarity with cloud platforms (AWS, GCP, or Azure) is a plus.
Skills
pythonmachine learningsqldocker