University of California , San Francisco
Research AI Tooling Lead Software Engineer
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Job at a Glance
- Category
- Software Developer
- Location
- San Francisco, California, United States
- Salary
- Check with seller
- Job Type
- Full Time
- Company
- University of California , San Francisco
- Status
- Open & Active
Job Description
Job Overview
Academic Research Services (ARS) serves the needs of the UCSF research community by providing an integrated repository of HIPAA compliant clinical and life sciences data and a centralized, secure, professionally managed infrastructure for the storage and management of research data.
We are seeking a highly skilled Research AI Tooling Lead Software Engineer to join our team. The ideal candidate will have expertise in AI/ML technologies, software architecture, and experience working with open-source libraries. They will be responsible for leading the development of AI tooling and creating reusable patterns that can be combined to produce production-ready products used by other teams.
Demonstrated knowledge of modern AI/ML technologies, including NLP, vectorization, inference models, generative adversarial networks, etc.
Demonstrated ability to interconnect existing open source or commercial software libraries using standardized API-driven processes.
Experience delivering platform-quality tools or experiences to a user community, preferably composed of researchers and/or developers.
Academic Research Services (ARS) serves the needs of the UCSF research community by providing an integrated repository of HIPAA compliant clinical and life sciences data and a centralized, secure, professionally managed infrastructure for the storage and management of research data.
We are seeking a highly skilled Research AI Tooling Lead Software Engineer to join our team. The ideal candidate will have expertise in AI/ML technologies, software architecture, and experience working with open-source libraries. They will be responsible for leading the development of AI tooling and creating reusable patterns that can be combined to produce production-ready products used by other teams.
Demonstrated knowledge of modern AI/ML technologies, including NLP, vectorization, inference models, generative adversarial networks, etc.
Demonstrated ability to interconnect existing open source or commercial software libraries using standardized API-driven processes.
Experience delivering platform-quality tools or experiences to a user community, preferably composed of researchers and/or developers.
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