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$36.8K

$112.3K

$185.6K

How much do reinforcement learning engineer jobs pay per year?

As of Aug 22, 2026, the average yearly pay for reinforcement learning engineer in Illinois is $112,276.00, according to ZipRecruiter salary data. Most workers in this role earn between $80,400.00 and $146,800.00 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 Illinois?

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

What job categories do people searching Reinforcement Learning Engineer jobs in Illinois look for?

The top searched job categories for Reinforcement Learning Engineer jobs in Illinois are:

What cities in Illinois are hiring for Reinforcement Learning Engineer jobs?

Cities in Illinois with the most Reinforcement Learning Engineer job openings:

Reinforcement Learning Engineer jobs near you
Infographic showing various Reinforcement Learning Engineer job openings in Illinois as of August 2026, with employment types broken down into 93% Full Time, and 7% Contract. Highlights an 93% In-person, and 7% Remote job distribution, with an average salary of $112,276 per year, or $54 per hour.

Autonomous Infrastructure and Robotic Science Lead

Argonne National Laboratory

Lemont, IL • On-site

Full-time

Re-posted 5 days ago

Job description

The Computing, Environment, and Life Sciences (CELS) Directorate seeks an outstanding scientist to lead and support frontier research at the intersection of AI, autonomous platforms, data infrastructure, and domain science. The candidate will have established expertise across automated and autonomous experimental platforms and AI in addition to leadership of multi-disciplinary research programs and the development of novel research concepts.

The scientist will lead Argonne's Rapid Prototyping Laboratory (RPL), a team of computer scientists, roboticists, data scientists, and subject matter experts, who develop hardware and software infrastructure for laboratory autonomy, support autonomous laboratories in domains including chemistry, biology, and quantum science, work with domain scientists to execute autonomous experiments, and advance laboratory autonomy and robotics.

RPL develops the open-source Modular Autonomous Discovery for Science (MADSci) software framework for the orchestration of autonomous laboratories in addition to software infrastructure supporting the operation, training, and execution of robotic workflows. The scientist would be responsible for directing activities towards the advancement of these internal capabilities in addition to the support and development of collaborations across Argonne and beyond.

Focus Areas (expertise in one or more is highly desirable):

  • Autonomous laboratories for chemistry, materials, biology, etc.
  • AI/ML for predictive modeling and inverse design
  • Generative models, reinforcement learning, and agent-based approaches to streamline experimentation and accelerate discovery
  • Integration of HPC, data infrastructure, and ML pipelines for data-driven and autonomous research
  • Digital twins and simulation-augmented AI tools

Key Responsibilities:

  • Guide the development of infrastructure for laboratory autonomy including physical autonomous laboratories, robotics laboratories, and software frameworks for autonomous science and robotics
  • Facilitate collaborations between the RPL and domain scientists across Argonne and partner institutions in the execution of successful autonomous science demonstrations
  • Facilitate collaborations between the RPL and teams at partner institutions developing autonomous science and robotics infrastructure
  • Guide the RPL team towards the advancement of laboratory autonomy and robotics
  • Publish in refereed journals and present at conferences, symposia, and seminars
  • Provide work direction and mentorship to postdoctoral appointees, research assistants, students, and technical staff
  • Execute all activities in compliance with Argonne's safety policies, Safeguards and Security policies, work rules, and safe practices

Position Requirements

  • Completed Ph.D. in Computer Science, Materials Science, Physics, Chemistry, or a related field, and a minimum of 4+ years of related experience
  • Proven research track record in deploying automated and autonomous platforms and AI/ML towards accelerating science
  • Demonstrated ability to formulate scientific problems relevant to the DOE portfolio
  • Strong oral and written communication skills, with the ability to work effectively with internal and external collaborators to achieve established goals
  • Demonstrated ability to collaborate in a multidisciplinary environment and provide scientific guidance to a diverse research community
  • Ability to model Argonne's core values of impact, safety, respect, integrity, and teamwork

Application Instructions:

Submit the following materials as attachments to your application:

  • Cover letter detailing how your experience and expertise align with and will contribute to this position
  • Curriculum vitae with publication list
  • 1-page research statement outlining proposed research directions

About Argonne and the Rapid Prototyping Lab


Argonne National Laboratory is a U.S. Department of Energy multidisciplinary science and engineering research center, operated by UChicago Argonne, LLC. Argonne tackles the largest scientific and engineering challenges of our time, from clean energy and advanced materials to artificial intelligence and quantum information science.

The Rapid Prototyping Lab (RPL), in the Data Science and Learning division, develops integrated hardware and software solutions to accelerate scientific discovery through robotics and AI. RPL serves as a software and robotics hub where scientists collaborate, train the next-generation autonomous-discovery workforce, and develop open-source infrastructure for self-driving labs. RPL projects span new materials for energy storage, discovery of antimicrobial compounds, isotope production for medical applications, and more.

MADSci is RPL's flagship open-source software ecosystem and a core enabling technology for Argonne's broader Autonomous Discovery initiative, which aims to transform laboratory science by combining robotics, AI, and simulation to design, execute, and learn from experiments at unprecedented scale.

For more information:

  • Rapid Prototyping Lab:https://rpl.cels.anl.gov/
  • Autonomous Discovery at Argonne:https://www.anl.gov/autonomous-discovery
  • MADSci on GitHub:https://github.com/AD-SDL/MADSci
  • AD-SDL organization on GitHub:https://github.com/AD-SDL

Job Family

Research Development (RD)

Job Profile

Computational Science 3

Worker Type

Regular

Time Type

Full timeThe expected hiring range for this position is $116,250.00 - $181,350.00.

Please note that the pay range information is a general guideline only. The pay offered to a selected candidate will be determined based on factors such as, but not limited to, the scope and responsibilities of the position, the qualifications of the selected candidate, business considerations, internal equity, and external market pay for comparable jobs. Additionally, comprehensive benefits are part of the total rewards package.

Click here to view Argonne employee benefits!

As an equal employment opportunity employer, and in accordance with our core values of impact, safety, respect, integrity and teamwork, Argonne National Laboratory is committed to a safe and welcoming workplace that fosters collaborative scientific discovery and innovation. Argonne encourages everyone to apply for employment. Argonne is committed to nondiscrimination and considers all qualified applicants for employment without regard to any characteristic protected by law.

Argonne employees, and certain guest researchers and contractors, are subject to particular restrictions related to participation in Foreign Government Sponsored or Affiliated Activities, as defined and detailed in United States Department of Energy Order 486.1A. You will be asked to disclose any such participation in the application phase for review by Argonne's Legal Department.

All Argonne offers of employment are contingent upon a background check that includes an assessment of criminal conviction history conducted on an individualized and case-by-case basis. Please be advised that Argonne positions require upon hire (or may require in the future) for the individual be to obtain a government access authorization that involves additional background check requirements. Failure to obtain or maintain such government access authorization could result in the withdrawal of a job offer or future termination of employment.

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