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Reinforcement Learning Engineer Jobs in Orem, UT

... continuous learning within the team. * Collaborate with cross-functional teams (engineering ... g., supervised, unsupervised, reinforcement learning, deep learning) and their practical ...

Senior Data Scientist

Lehi, UT · On-site

$180 - $250/hr

... continuous learning within the team. * Collaborate with cross-functional teams (engineering ... g., supervised, unsupervised, reinforcement learning, deep learning) and their practical ...

... continuous learning within the team. * Collaborate with cross-functional teams (engineering ... g., supervised, unsupervised, reinforcement learning, deep learning) and their practical ...

... continuous learning within the team. * Collaborate with cross-functional teams (engineering ... g., supervised, unsupervised, reinforcement learning, deep learning) and their practical ...

... 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 ...

... 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 ...

... 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 ...

Reinforcement Learning Engineer information

See Orem, UT salary details

$33K

$100.7K

$166.5K

How much do reinforcement learning engineer jobs pay per year?

As of Aug 22, 2026, the average yearly pay for reinforcement learning engineer in Orem, UT is $100,729.00, according to ZipRecruiter salary data. Most workers in this role earn between $72,200.00 and $131,700.00 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 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 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 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 Orem, UT?

For Reinforcement Learning Engineer jobs in Orem, UT, the most frequently searched job titles are:

Infographic showing various Reinforcement Learning Engineer job openings in Orem, UT as of August 2026, with employment types broken down into 92% Full Time, and 8% Contract. Highlights an 93% In-person, and 7% Remote job distribution, with an average salary of $100,729 per year, or $48.4 per hour.

Full-time

Medical, Retirement, PTO

Posted 10 days ago


Job description

ABOUT THIS POSITION

Designs, develops and programs methods, processes, and systems to consolidate and analyze unstructured, diverse "big data" sources to generate actionable insights and solutions for client services and product enhancement. Interacts with product and service teams to identify questions and issues for data analysis and experiments. Develops and codes software programs, algorithms and automated processes to cleanse, integrate and evaluate large datasets from multiple disparate sources. Identifies meaningful insights from large data and metadata sources; interprets and communicates insights and findings from analysis and experiments to product, service, and business managers. Incumbents whose primary role is technical and focused on data storage, warehousing and systems architecture should be matched to Database Engineering or Storage Engineering. Incumbents whose focus is the quantitative analysis of complex business problems and issues using data from internal and external sources to provide insight to decision-makers should be matched to Business Intelligence. Incumbents whose primary role is technical and focused on designing and building system-generated reports, reporting tools and dashboards for data generation should be matched to Data Informatics. Incumbents whose focus is primarily on experimental design and advanced or complex statistical analysis and modeling of datasets should be matched to Statistician/Mathematician. This is a product engineering role in which employees work with multiple types of business data. Incumbents whose focus is primarily on analysis and modeling of financial, marketing or pricing data should be matched to Finance, Market Research or Pricing as appropriate. May be internal operations-focused or external client-focused, working in conjunction with Professional Services and outsourcing functions.

WHAT YOU'LL DO

* Lead the design, development, and implementation of sophisticated machine learning models and predictive analytics solutions to solve critical business problems.
* Mentor and guide junior data scientists, fostering a culture of excellence and continuous learning within the team.
* Collaborate with cross-functional teams (engineering, product, business stakeholders) to define data science project requirements, scope, and deliverables.
* Conduct in-depth data exploration, analysis, and visualization to identify trends, patterns, and anomalies, presenting findings clearly and concisely to diverse audiences.
* Develop and maintain robust data pipelines and infrastructure in collaboration with data engineers to ensure data quality, accessibility, and integrity.
* Stay abreast of the latest advancements in data science, machine learning, and artificial intelligence, evaluating and recommending new technologies and methodologies.
* Contribute to the strategic direction of Waystar's data science initiatives, identifying opportunities for innovation and impact.
* Champion data-driven decision-making throughout the company, educating and influencing stakeholders on the power of data science.
* Evaluate and select appropriate statistical methods and machine learning algorithms for various business challenges, ensuring rigor and validity.

WHAT YOU'LL NEED

* Master's or Ph.D. in Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field.
* 8+ years of progressive experience in data science, with a proven track record of delivering impactful data-driven solutions in a fast-paced environment.
* Expert-level proficiency in Python and/or R for data manipulation, statistical analysis, and machine learning model development.
* Extensive experience with various machine learning techniques (e.g., supervised, unsupervised, reinforcement learning, deep learning) and their practical applications.
* Strong understanding of statistical modeling, experimental design, hypothesis testing, and causal inference.
* Proficiency in SQL for data querying and manipulation, with experience working with large-scale datasets.
* Experience with cloud platforms (e.g., AWS, Azure, GCP) and big data technologies (e.g., Spark, Hadoop) is highly desirable.
* Excellent communication, presentation, and interpersonal skills, with the ability to explain complex technical concepts to non-technical stakeholders.
* Demonstrated ability to lead projects, mentor team members, and drive successful outcomes.
* Prior experience in the healthcare technology or financial services industry is a plus.

ABOUT WAYSTAR

Through a smart platform and better experience, Waystar helps providers simplify healthcare payments and yield powerful results throughout the complete revenue cycle.

Waystar's healthcare payments platform combines innovative, cloud-based technology, robust data, and unparalleled client support to streamline workflows and improve financials so providers can focus on what matters most: their patients and communities. Waystar is trusted by 1M+ providers, 1K+ hospitals and health systems, and is connected to over 5K commercial and Medicaid/Medicare payers. We are deeply committed to living out our organizational values: honesty; kindness; passion; curiosity; fanatical focus; best work, always; making it happen; and joyful,optimistic & fun.

Waystar products have won multiple Best in KLAS or Category Leader awards since 2010 and earned multiple #1 rankings from Black Book surveys since 2012. The Waystar platform supports more than 500,000 providers, 1,000 health systems and hospitals, and 5,000 payers and health plans. For more information, visit waystar.comor follow @Waystaron Twitter.

WAYSTAR PERKS

  • Competitive total rewards (base salary + bonus, if applicable)
  • Customizable benefits package (3 medical plans with Health Saving Account company match)
  • We offer generous paid time off for our non-exempt team members, starting with 3 weeks +13 paid holidays, including 2 personal floating holidays. We also offer flexible time off for our exempt team members + 13 paid holidays
  • Paid parental leave (including maternity + paternity leave)
  • Education assistance opportunities and free LinkedIn Learning access
  • Free mental health and family planning programs, including adoption assistance and fertility support
  • 401(K) program with company match
  • Pet insurance
  • Employee resource groups

Waystar is proud to be an equal opportunity workplace. We celebrate, value, and support diversity and inclusion. Qualified applicants will receive consideration for employment without regard to race, color, religion, age, sex, national origin, disability status, genetics, marital status, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws.

This applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.