Senior Machine Learning Engineer
University of Utah Health · Salt Lake City Metropolitan Area · 1 mo ago
EngineeringFull-time
Responsibilities
- Create, manage, maintain, and refactor ML codebases, pipelines, and workflows for the innovation office.
- Collaborate closely with research, medical, and engineering staff to design and implement ML approaches.
- Implement scalable ML methods and workflows for high-performance computing (HPC) resources, in close collaboration with research staff and technical staff.
- Review code developed by other developers and provide feedback to ensure best practices (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
- Troubleshoot data analysis issues, including implementation issues, hyper-parameter choices, and modeling decisions.
- Assist in preparation of manuscripts and dissemination of results in the appropriate venues.
- Conduct tasks independently and communicate optimally to team members and stakeholders.
- Develop deployable solutions for the health care system.
Qualifications
- Bachelor’s degree in a relevant field.
- 5 years of experience in software engineering.
Preferred Qualifications
- Experience working in complex academic medical center environments.
- Experience with large multimodal health datasets.
- Experience with lifecycle management in a fast-paced software environment.
- Experience in shipping products and scalable, reliable services.
- Hands-on experience with asynchronous programming and concurrency (threads, tasks, futures, async/await).
- Experience with Azure Kubernetes Service (AKS), Amazon Elastic Kubernetes Service (EKS), and/or Google Kubernetes Engine (GKE).
- Experience with database engines, query engines, indexing solutions (columnar, full-text, vector), at scale.
- Experience with programming CUDA, AI systems at scale.
- Experience with live site operations, Site Reliability Engineering (SRE) or production support roles.
- Experience in networking, distributed systems, lower-level infrastructure.
- Experience developing accessible technologies.
- Proficiency in code and system health, diagnosis and resolution, and software test engineering.
- Experience with AI agents.