Machine Learning Engineer
United States of America
Full-time
2 weeks ago
$132,000 - $180,000 USD
H1B Sponsor Likely
Key skills
MLOpsPythonSQLAI/ML pipelinesETL pipelinesCloud architectureData infrastructureEpic data modelsCommunication skillsProblem-solving skillsProject managementAIArtificial IntelligenceMachine LearningMLGenerative AIGenAILarge Language ModelsPyTorchscikit-learnPandasNumPyJupyterETLData WarehousingTableauAWSAzureGCPPostgreSQLCI/CDLeadershipCommunication
About this role
The University of California, San Francisco (UCSF) is a leading university dedicated to promoting health worldwide through advanced biomedical research. They are seeking a Machine Learning Engineer to lead the development and maintenance of data pipelines for AI/ML tools, collaborating with various technical teams to implement customized research solutions.
Responsibilities:
- Lead the development, implementation, and maintenance of data pipelines and infrastructure to support the deployment and continuous monitoring of Machine Learning (ML) and generative Artificial Intelligence (AI) tools
- Manage and optimize the data and monitoring pipelines of the Health IT Platform for Advanced Computing (HIPAC)
- Work on implementing new data integrations, enhancing HIPAC’s ETL functionalities, productionizing AI/ML tools developed by UCSF data scientists/researchers, and designing and implementing metrics to continuously monitor AI/ML tools deployed at UCSF Health
Requirements:
- Bachelor's degree in Computer Science, Computer Engineering, or related area and/or equivalent experience/training
- 5+ years of experience in positions of increasing responsibility designing, implementing, and maintaining complex AI/ML applications
- Advanced experience with Python; ability to write clean, efficient, and production-level Python code
- Advanced experience with SQL (e.g., SQLServer, PostgreSQL)
- Experience with data analysis and machine learning tools such as Jupyter, Pandas, scikit-learn, Numpy/Scipy, PyTorch, etc
- Demonstrated advanced knowledge of full software development lifecycle
- Demonstrated experience deploying, monitoring, and maintaining AI/ML models and pipelines
- Advanced experience in database systems, data warehousing solutions, and understanding of ETL pipelines
- Advanced experience in designing, building, or maintaining data infrastructure for efficient ML model training and inference
- Demonstrated experience working with MLOps, DevOps, and CI/CD pipeline toolsets
- Experience in developing complex, automated testing
- Experience with cloud-based architecture in platforms such as AWS, GCP, Azure
- Demonstrated effective communication and interpersonal skills
- Demonstrated ability to communicate technical information to technical and non-technical personnel at various levels in the organization
- Self-motivated and works independently and as part of a team. Able to learn effectively and meet deadlines
- Demonstrated broad problem-solving skills
- Demonstrated ability to interface with management on a regular basis
- Excellent project leadership and management skills
- Master's Degree or PhD in Computer Science, Computer Engineering, or related area and / or equivalent experience / training
- Epic Clarity Certification
- Cloud Development certifications
- Experience with large language models and other generative AI technologies, especially supporting the deployment of GenAI-based tools in a production environment
- Familiar with data visualization tools (e.g., Tableau)
- Experience with Epic data structures