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Reinforcement Learning Engineer Jobs in Utah (NOW HIRING)

Super Soccer Stars

Youth Soccer Coach

Vineyard, UT

... imaginative learning and physical activity. We are looking to hire an energetic and fun-loving ... Youth Athletes United was created to provide the best programming and service in the market for ...

Super Soccer Stars

Youth Soccer Coach

Vineyard, UT · On-site

... imaginative learning and physical activity. We are looking to hire an energetic and fun-loving ... Youth Athletes United was created to provide the best programming and service in the market for ...

Super Soccer Stars

Youth Soccer Coach

Vineyard, UT · On-site

... imaginative learning and physical activity. We are looking to hire an energetic and fun-loving ... Youth Athletes United was created to provide the best programming and service in the market for ...

All JobsReinforcement Learning Engineer JobsReinforcement Learning Engineer Jobs in Utah

Reinforcement Learning Engineer information

See Utah salary details

$34.6K

$105.5K

$174.3K

How much do reinforcement learning engineer jobs pay per year?

As of Aug 12, 2026, the average yearly pay for reinforcement learning engineer in Utah is $105,480.00, according to ZipRecruiter salary data. Most workers in this role earn between $75,600.00 and $137,900.00 per year, depending on experience, location, and employer.

What is a reinforcement learning engineer?

Reinforcement Learning Engineers are specialized professionals who design, develop, and implement algorithms based on reinforcement learning, a type of machine learning where agents learn to make decisions by receiving rewards or penalties. They work on building models that enable machines to learn optimal actions through trial and error in complex environments. Their responsibilities often include developing RL architectures, tuning hyperparameters, running simulations, and applying RL methods to real-world problems like robotics, gaming, or recommendation systems. RL Engineers typically have strong backgrounds in computer science, mathematics, and deep learning, along with experience in programming languages like Python and frameworks such as TensorFlow or PyTorch.

What are the key skills and qualifications needed to thrive as a reinforcement learning engineer, and why are they important?

To thrive as a Reinforcement Learning Engineer, you need a strong background in machine learning, mathematics (especially probability and statistics), and programming languages like Python, often supported by a relevant degree in computer science or engineering. Familiarity with deep learning frameworks (such as TensorFlow or PyTorch), RL libraries (like OpenAI Gym), and cloud computing platforms is typically required. Problem-solving skills, creativity, and effective collaboration help set outstanding engineers apart in this field. These competencies enable the design and deployment of advanced RL solutions that address real-world challenges and drive innovation.

What are some common challenges faced by reinforcement learning engineers when deploying models in real-world environments?

One of the main challenges Reinforcement Learning (RL) Engineers face is bridging the gap between simulation and real-world deployment. Models that perform well in controlled environments may struggle with unpredictable data, safety constraints, or limited feedback in production. Additionally, RL algorithms often require significant computational resources and careful tuning to avoid instability. Collaboration with domain experts and software engineers is essential to address these issues and ensure successful integration of RL solutions into existing systems.

What is the difference between Reinforcement Learning Engineer vs Machine Learning Engineer?

AspectReinforcement Learning EngineerMachine Learning Engineer
CredentialsBachelor's/Master's in CS, AI, or related; experience with RL frameworksBachelor's/Master's in CS, Data Science, or related; experience with ML algorithms
Work EnvironmentResearch labs, AI startups, tech companies focusing on RL applicationsTech companies, data-driven firms, AI departments across industries
Industry UsageSpecialized in RL projects like robotics, game AI, autonomous systemsBroader applications including predictive modeling, NLP, computer vision

Reinforcement Learning Engineers focus on developing algorithms that learn through interactions with environments, often in robotics or gaming. Machine Learning Engineers work on a wider range of models and applications. While both roles require strong programming and math skills, RL Engineers specialize in sequential decision-making, whereas ML Engineers handle diverse data-driven tasks across industries.

What are popular job titles related to Reinforcement Learning Engineer jobs in Utah? For Reinforcement Learning Engineer jobs in Utah, the most frequently searched job titles are:
What job categories do people searching Reinforcement Learning Engineer jobs in Utah look for? The top searched job categories for Reinforcement Learning Engineer jobs in Utah are:
What cities in Utah are hiring for Reinforcement Learning Engineer jobs? Cities in Utah with the most Reinforcement Learning Engineer job openings:
Reinforcement Learning Engineer jobs near you
Infographic showing various Reinforcement Learning Engineer job openings in Utah as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 22% Part Time, 1% Temporary, and 2% Contract. Highlights an 89% Physical, 2% Hybrid, and 9% Remote job distribution, with an average salary of $105,480 per year, or $50.7 per hour.

Senior Machine Learning Engineer

University of Utah Health

Salt Lake City, UT • On-site

$101K - $138K/yr

Full-time

Medical, Dental, Life, Retirement, PTO

Re-posted 9 days ago

University Of Utah Health rating

7.7

Company rating: 7.7 out of 10

Based on 142 frontline employees who took The Breakroom Quiz

157th of 887 rated healthcare providers

Job description

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

Corporate Overview: University of Utah Health is an integrated academic healthcare system with five hospitals including a level 1 trauma center, eleven community health centers, over 1,600 providers, and a health plan serving over 200,000 members. University of Utah Health is nationally ranked and recognized for our academic research, quality standards and overall patient experience. In addition to our clinical delivery system, we have a School of Medicine, School of Dentistry, College of Nursing, College of Pharmacy, and College of Health providing education and training for over 1,250 providers annually. We have over 2 million patient visits annually and research grants exceeding $350 million. University of Utah Hospitals and Clinics represents our clinical operations for the larger health system.
As a patient-focused organization, University of Utah Health exists to enhance the health and well-being of people through patient care, research and education. Success in this mission requires a culture of collaboration, excellence, leadership, and respect. University of Utah Health seeks staff that are committed to the values of compassion, collaboration, innovation, responsibility, integrity, quality and trust that are integral to our mission. EO/AA
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.

#MachineLearningEngineer
#MLEngineering
#MLPlatform
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

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