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Reinforcement Learning Engineer Jobs in Independence, MO

Imperial PFS

Senior Security AI Engineer

Kansas City, MO · On-site

$111K - $153K/yr

... reinforcement learning. Preferred : • Experience securing LLMs, vector databases, model APIs, and AI agents. • Knowledge of NIST AI RMF, ISO/IEC 42001, EU AI Act, or similar AI governance ...

Imperial PFS

Senior Security AI Engineer

Kansas City, MO · On-site

$111K - $153K/yr

... reinforcement learning. Required Qualifications • 7+ years of experience in cybersecurity engineering, architecture, or related roles. • Strong knowledge of cloud security (AWS, Azure, or GCP ...

Garmin Ltd.

Data Scientist 2

Olathe, KS · On-site

$110 - $160/hr

... apply machine learning, statistical analysis, and data engineering techniques to address ... reinforcement learning) * Hands‑on experience with MLOps, model deployment, and CI/CD for data ...

Propio

AI/LLM Safety Engineer

Leawood, KS · On-site

Conduct safety reviews of reinforcement-learning (RL) environments and trajectory data, partnering with environment and agent engineering teams to embed safety constraints directly into the ...

Propio

AI/LLM Safety Engineer

Overland Park, KS

Conduct safety reviews of reinforcement-learning (RL) environments and trajectory data, partnering with environment and agent engineering teams to embed safety constraints directly into the ...

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All JobsReinforcement Learning Engineer JobsReinforcement Learning Engineer Jobs in Independence, MO

Reinforcement Learning Engineer information

See Independence, MO salary details

$34.6K

$105.6K

$174.6K

How much do reinforcement learning engineer jobs pay per year?

As of Aug 14, 2026, the average yearly pay for reinforcement learning engineer in Independence, MO is $105,640.00, according to ZipRecruiter salary data. Most workers in this role earn between $75,700.00 and $138,100.00 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 Independence, MO?

For Reinforcement Learning Engineer jobs in Independence, MO, the most frequently searched job titles are:

What job categories do people searching Reinforcement Learning Engineer jobs in Independence, MO look for?

The top searched job categories for Reinforcement Learning Engineer jobs in Independence, MO are:

What cities near Independence, MO are hiring for Reinforcement Learning Engineer jobs?

Cities near Independence, MO with the most Reinforcement Learning Engineer job openings:

Reinforcement Learning Engineer jobs near you
Infographic showing various Reinforcement Learning Engineer job openings in Independence, MO as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $105,640 per year, or $50.8 per hour.

Machine Learning Engineer Principal

The University of Kansas Health System

Mission, KS • On-site

Full-time

Re-posted 9 days ago

University Of Kansas Health System rating

7.5

Company rating: 7.5 out of 10

Based on 177 frontline employees who took The Breakroom Quiz

234th of 887 rated healthcare providers

Job description

Position Title
Machine Learning Engineer Principal
Broadmoor Campus
Position Summary / Career Interest:
The Machine Learning Engineer (MLEA) Principal will lead research and development efforts to advance machine learning applications within a hospital setting. This role is also responsible for developing innovative algorithms and models to improve patient care, operational efficiency, and clinical outcomes. This role requires extensive expertise in machine learning, cloud deployment, and data engineering, with a strong emphasis on applied research and experimentation.
Responsibilities and Essential Job Functions
  • Lead and conduct advanced research in machine learning and artificial intelligence to develop novel algorithms and methodologies tailored to healthcare applications.
  • Design and implement experiments to test and validate new machine learning models and techniques, focusing on improving patient care and hospital operations.
  • Lead methodological research and implementation of methods to adjust for data set shift for healthcare applications
  • Collaborate with clinical staff, academic institutions, research labs, and industry partners to stay at the cutting edge of machine learning research and its applications in healthcare.
  • Publish research findings in top-tier conferences and journals, and present at industry events and seminars.
  • Develop and deploy state-of-the-art machine learning models using iterative development processes, based on statistical approaches and data mining techniques.
  • Identify and implement the most optimal modeling techniques based on available data types and objectives/use cases (supervised, unsupervised, semi-supervised, or reinforcement learning).
  • Implement highly efficient automated processes that produce modeling results at scale.
  • Review current offerings and future developments in artificial intelligence and machine learning and socialize these with key stakeholders to understand needs and potential use cases in the hospital.
  • Perform validation of machine learning models for accuracy and develop recommendations for enhancements based on localized data, monitor their performance post-implementation, and fine-tune for optimal results.
  • Create clear documentation of workflows, methodologies used, and assumptions built in for various levels of technical expertise.
  • Engage in the deployment and integration of predictive models and artificial intelligence into development and production environments within the hospital.
  • Advance the department's capabilities in technical and analytical areas by proactively building partnerships and collaborating with cross-functional teams.
  • Contribute to a culture of innovation, collaboration, and continuous improvement by following the latest developments in machine learning research and technology trends.
  • Able to expertly maintain existing models as well as deployment new models in both Epic and Non-Epic environments
  • Stay up to date with the latest changes from Epic to their analytics and predictive modeling applications through (e.g.) Nova Notes
  • Must be able to perform the professional, clinical and or technical competencies of the assigned unit or department.
  • These statements are intended to describe the essential functions of the job and are not intended to be an exhaustive list of all responsibilities. Skills and duties may vary dependent upon your department or unit. Other duties may be assigned as required.

Required Education and Experience
  • Bachelors Degree in Computer Science, Mathematics, Statistics, Engineering, Economics, or another computational/quantitative field (or equivalent experience)
  • 7 or more years of experience using data mining/analytical methods and associated tools such as Python, R, etc.
  • 7 or more years of experience with SQL in a relational database or an equivalent combination of education and experience
  • 5 or more years of experience with various machine learning methods: unsupervised learning, semi-supervised, supervised learning, as well as anomaly detection, natural language processing and dimensionality reduction
  • 5 or more years of experience with containerization and orchestration tools such as Docker and Kubernetes
  • 5 or more years of experience with cloud computing platforms such as Azure
  • 3 or more years of experience with Nebula, Epic's cloud computing and modeling platform

Preferred Education and Experience
  • Master's Degree in a related field OR
  • Doctorate in a related field
  • Experience working with business intelligence tools such as Power BI, Qlik, SAP Business Objects, Tableau, etc.
  • Experience with analytical documentation tools such as Jupyter Notebook
  • Experience in a relevant industry or environment

Required Licensure and Certification
  • Epic certification in 4 data model(s). If not certified, certification is required within 12 months from employment within 1 Year

Time Type:
Full time
Job Requisition ID:
R-52607
Important information for you to know as you apply:
  • The health system is an equal employment opportunity employer. Qualified applicants are considered for employment without regard to race, color, religion, sex (including pregnancy, gender identity, and sexual orientation), national origin, ancestry, age, disability, veteran status, genetic information, or any other legally-protected status. See also Diversity, Equity & Inclusion.
  • The health system provides reasonable accommodations to qualified individuals with disabilities. If you need to request reasonable accommodations for your disability as you navigate the recruitment process, please let our recruiters know by requesting an Accommodation Request form using this link asktalentacquisition@kumc.edu.
  • Employment with the health system is contingent upon, among other things, agreeing to the health-system-dispute-resolution-program.pdf and signing the agreement to the DRP.

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About University of Kansas Health System

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Operating within the healthcare industry, The University of Kansas Health System is a renowned medical institution located in Kansas City, KS, United States. Established in 1905, this not-for-profit health system has evolved to offer an extensive range of products and services, which spans across a variety of specialist areas such as cancer care, neurology, cardiology, and organ transplants, among others. The core mission of The University of Kansas Health System is to enhance the health and wellness of individuals and communities by providing world-class healthcare services, quality education and conducting advanced research. They are also known for their unwavering commitment to academic medicine, which sets them apart from their peers.

Industry

Health care and social assistance

Company size

5,001 - 10,000 Employees

Headquarters location

Kansas City, KS, US

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