ZipRecruiter

Log In

1

Reinforcement Learning Engineer Jobs in Illinois

Tagup

Senior Software Engineer

Virginia, IL · On-site

$120K - $158K/yr

We're a team of engineers and data scientists driven by our mission to use reinforcement learning and probabilistic modeling to optimize military logistics and critical infrastructure, ensuring our ...

Braze

Staff Software Engineer

Chicago, IL · On-site

$184K - $299K/yr

WHAT YOU'LL DO As a Staff Engineer on Braze's AI Decisioning Experience team, you will play a pivotal role in shaping the future of our AI decisioning (reinforcement learning-based personalization ...

Elevance Health

Principal Applied Scientist

Chicago, IL · On-site

$214K - $350K/yr

Mentors data scientists, machine learning engineers, researchers, and technical leaders. Minimum ... Experience with generative artificial intelligence, large language models, reinforcement learning ...

JPMorgan Chase & Co.

Applied AI/ML Lead

Chicago, IL · On-site

You will be a part of an innovative team, working closely with our product owners, data engineers ... Published research in areas of Machine Learning, Deep Learning or Reinforcement Learning at a major ...

Fairygodboss

Applied AI/ML - Vice President

Chicago, IL · On-site

Work with Product Owners and Software Engineers to productionize the models and Partners closely ... Published research in areas of Machine Learning, Deep Learning or Reinforcement Learning at a major ...

CDW LLC.

Principal Consultant- AWS

Vernon Hills, IL · On-site

$156K - $240K/yr

Providing Engineering Services for AWS, coordinating engagement strategies, and qualifying ... learning, unsupervised learning, reinforcement learning, deep learning, and natural language ...

previous page

Showing results 41-60

All JobsReinforcement Learning Engineer JobsReinforcement Learning Engineer Jobs in Illinois

Reinforcement Learning Engineer information

See Illinois salary details

$36.8K

$112.3K

$185.6K

How much do reinforcement learning engineer jobs pay per year?

As of Sep 12, 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 1% As Needed, 72% Full Time, 26% Part Time, and 1% Contract. Highlights an 83% Physical, 3% Hybrid, and 14% Remote job distribution, with an average salary of $112,276 per year, or $54 per hour.

Machine Learning PhD Student, Frontier AI Evaluation (Contract)

Mundelein, IL • On-site

Cobalt
See more jobs at Cobaltexternal

Other

This job post has expired 2 days ago. Applications are no longer accepted.

Job description

About the role:

Cobalt is seeking current PhD students working in machine learning to produce the expert reasoning and evaluation data used to train and assess frontier AI models.

This opportunity is suited to students who are actively doing ML research: designing and running experiments, training and evaluating models, working through derivations, and debugging results that do not behave as expected. You may be at any stage of your program, from first year through writing up, and you do not need to have published yet.

You do not need prior experience in data annotation or model evaluation. What matters is that you can solve non-trivial ML problems unaided and explain your reasoning clearly in writing.


What you'll do:

Depending on the project, you may:

  • Produce written reasoning traces on hard ML problems, capturing how you reach a solution rather than only the solution itself, and draft expert reference answers to technical questions
  • Author novel problems in your subfield that have verifiable or defensible correct answers
  • Evaluate model-generated technical content: compare and rank responses, articulate what makes the stronger one stronger, and identify the specific step at which a chain of reasoning breaks down
  • Assess whether stated conclusions are supported by the underlying derivation, code, or experimental evidence
  • Design rubrics and partial-credit criteria for scoring multistep technical tasks

Projects follow their own guidelines, formatting conventions, and quality standards, and you will work with feedback from reviewers and lab research teams.


Required qualifications:

  • Current enrollment in a PhD program in machine learning, computer science, statistics, mathematics, physics, or a closely related quantitative discipline, with research that is substantially ML focused, at any stage
  • Demonstrated depth in at least one area, for example optimization, reinforcement learning, language model training and post-training, learning theory, probabilistic methods, computer vision, natural language processing, or systems for ML
  • Ability to solve advanced ML problems independently, to interpret papers, derivations, code and experimental results, and to explain each step of your reasoning clearly in writing
  • Strong attention to detail, a commitment to factual accuracy, and the ability to work independently to agreed timelines
  • Confirmation that outside contract work is permitted under your visa status, funding terms, and institutional policies. Applicants are responsible for verifying this, and we cannot advise on it.

Publications at venues such as NeurIPS, ICML, ICLR, ACL, or CVPR are useful but not required, as is teaching assistant, grading, or peer review experience.


Why join Cobalt AI:

  • Advance frontier AI where it counts. Apply your expertise to data that frontier labs cannot obtain any other way, where your reasoning directly shapes how the next generation of models works through technical problems.
  • Grow professionally. Expand your influence through evaluation projects, advisory roles, and research collaborations, while developing a working understanding of how frontier models are trained and assessed.
  • Work with a top-tier network. Collaborate with researchers and engineers from leading institutions and labs on high-impact, flexible work.
  • Set your own schedule. Flexible 10 to 40 hour weeks that fit around your existing work and your life.
  • Competitive pay. Rates vary by project and are determined by a number of factors, including scope, skillset, and experience.

Apply