Senior Machine Learning Engineer

Overview

The Chief Innovation Office (CIO) at University of Utah Health (U of U Health) would serve as the strategic hub for advancing healthcare innovation, digital transformation, research commercialization, and new models of patient care. The office would connect clinical operations, research, education, and technology to accelerate the delivery of innovative solutions that improve health outcomes, patient experiences, and operational efficiency.

• Senior Machine Learning Engineers leverage their engineering expertise to solve a variety of technical problems for some of the most challenging and impactful projects in healthcare informatics and machine learning.
• You will work on a specific project critical to our needs with the opportunity to switch teams and projects as you and our fast-paced business grow. We need machine learning engineers who are versatile, rigorous, display leadership qualities and are enthusiastic to take on new problems.
• You will design, develop, test, deploy, maintain and enhance machine learning and AI solutions.
• You will be part of the Innovation Office, a product factory inside the health system of the University of Utah.

Location: 102 Tower (Downtown SLC)

Schedule: Monday - Friday 9 AM - 5 PM

Benefits:

• Save 50% on Tuition (Tuition reduced for eligible employees attending the University of Utah)
• Health Coverage, Dental Coverage, Life Insurance
• Retirement
• Paid Time Off
• 11 Paid Holidays per year

Please Note: This position requires participation in onsite interviews in Salt Lake City, Utah. We encourage applicants to apply only if they are comfortable with an in-person interview process and working closely with cross-functional teams.

We encourage candidates to submit resumes that accurately reflect their own skills, experience, and accomplishments. The information provided during the application process must be truthful and authentic, as qualifications may be verified during the hiring process.

Responsibilities

Essential Functions

• Creating, managing, maintaining, and refactoring ML codebases, pipelines, and workflows for the innovation office.
• Collaborating closely with research, medical, and engineering staff to design and implement ML approaches.
• Implementing 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).
• Troubleshooting data analysis issues, including implementation issues, hyper-parameter choices and modeling decision.
• Assisting in preparation of manuscripts and dissemination of results in the appropriate venues.
• Conducing tasks independently and communicate optimally to team members and stakeholders.
• Developing deployable solutions for the health care system.

Knowledge / Skills / Abilities

• Hands-on coding in C++, Python, PyTorch, or Tensorflow.

• Foundational understanding of supervised and unsupervised learning, reinforcement learning, and machine learning.

• Independently execute in the face of ambiguity

• Leads identifications of dependencies and the development of design documents for a product, application, service, or platform.

• Write efficient systems code and tests and able to debug distributed systems.

• Work on-call to monitor systems/product/service for degradation, downtime or interruptions.

• Innovative mindset with a keen eye for identifying opportunities for improvement.

• Ability to thrive in a fast-paced, dynamic environment and simultaneously handle multiple projects.

• Partner effectively with other engineers, product managers, and stakeholders.

Qualifications

Required

• Bachelor's degree in a relevant field.
• 5 years of experience in software engineering.

Qualifications (Preferred)

Preferred

• 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 in building 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.

Working Conditions and Physical Demands

Employee must be able to meet the following requirements with or without an accommodation.

• This is a sedentary position that may exert up to 10 pounds and may lift, carry, push, pull or otherwise move objects. This position involves sitting most of the time and is not exposed to adverse environmental conditions.

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Physical Requirements

Carrying, Climbing, Color Determination, Crawling, Far Vision, Lifting, Listening, Manual Dexterity, Near Vision, Pulling and/or Pushing, Reaching, Sitting, Speaking, Standing, Stooping and Crouching, Tasting or Smelling, Walking