Machine Learning Engineer

Machine Learning Engineer

IT EDW Operations

Full Time

87012BR

Job Summary

The Machine Learning and Data engineer role will 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 within UCSF's APeX Enabled Research (AER) team. Most projects will be in partnership with other UCSF technical teams and involve highly customized research solutions. Communication skills and inventive technical solutioning are crucial.

• Development of EHR-based interventions via clinical trials embedded within healthcare delivery systems to generate scientific evidence while delivering healthcare.
• Enabling UCSF researchers with algorithms, digital tools and / or clinical interventions with strong evidence of feasibility and acceptability.
• Develop technical approaches and budgets in order to implement these tools within the electronic medical record.
• Supporting the development of scalable, low cost infrastructure to enable ongoing research.
• Assisting in the design, implementation, and monitoring of AI / ML tools and related metrics.

This role primarily involves managing and optimizing the data and monitoring pipelines of the Health IT Platform for Advanced Computing (HIPAC), a cloud infrastructure that supports the development and deployment of AI / ML tools, including large language models (LLMs) in the EHR. The ML / data engineer will 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.

Competitive applicants for this position are software, machine learning, or data engineers with 5+ years of experience in implementing and maintaining AI / ML pipelines. Proficiency in MLOps, Python, SQL, and CI / CD is required. This role also requires a deep understanding of Epic data models (Clarity and Caboodle). Successful candidates either have or are able to obtain Epic Clinical / Clarity data model certification shortly after onboarding.

The final salary and offer components are subject to additional approvals based on UC policy. Your placement within the salary range is dependent on a number of factors including your work experience and internal equity within this position classification at UCSF. For positions that are represented by a labor union, placement within the salary range will be guided by the rules in the collective bargaining agreement. The salary range for this position is $132,000 - $197,900 (Annual Rate).

To learn more about the benefits of working at UCSF, including total compensation, please visit : https : / / ucnet.universityofcalifornia.edu / compensation-and-benefits / index.html

Department Description

The University of California, San Francisco (UCSF) Department of Information Technology Academic Research Systems (ARS) group is chartered to provide data services and infrastructure that support the UCSF Research Community's computing and analytic requirements through centralized informatics services in the areas of Data, Tools, Secure Compute Environments, and Consulting Services.

Required Qualifications

Preferred Qualifications

Equal Employment Opportunity

The University of California is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, protected veteran status, or other protected status under state or federal law.

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