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Reinforcement Learning Engineer Jobs in Chicago, IL

Skill Sprout

Physical Therapist

Northbrook, IL · On-site

$1.6K - $2.1K/wk

... programming and parent education as needed Utilizes principles of positive reinforcement and basic behavioral interventions to support client performance and learning. Acts as mentor to therapists ...

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All JobsReinforcement Learning Engineer JobsReinforcement Learning Engineer Jobs in Chicago, IL

Reinforcement Learning Engineer information

See Chicago, IL salary details

$39.1K

$119.4K

$197.3K

How much do reinforcement learning engineer jobs pay per year?

As of Aug 7, 2026, the average yearly pay for reinforcement learning engineer in Chicago, IL is $119,357.00, according to ZipRecruiter salary data. Most workers in this role earn between $85,500.00 and $156,100.00 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 Chicago, IL? For Reinforcement Learning Engineer jobs in Chicago, IL, the most frequently searched job titles are:
What job categories do people searching Reinforcement Learning Engineer jobs in Chicago, IL look for? The top searched job categories for Reinforcement Learning Engineer jobs in Chicago, IL are:
What cities near Chicago, IL are hiring for Reinforcement Learning Engineer jobs? Cities near Chicago, IL with the most Reinforcement Learning Engineer job openings:
Reinforcement Learning Engineer jobs near you
Infographic showing various Reinforcement Learning Engineer job openings in Chicago, IL 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 $119,357 per year, or $57.4 per hour.

Product Manager - AI Scheduling & Facilities

Uber Freight

Chicago, IL

Full-time

Medical, Dental, Vision, Life, Retirement

Re-posted 13 hours ago

Uber Freight rating

7.3

Company rating: 7.3 out of 10

Based on 23 frontline employees who took The Breakroom Quiz

167th of 359 rated logistics

Job description

Schedule: Full Time
Job Type: Hybrid
Salary Type: Salary
Req #2747

About the Role 

Uber Freight connects shippers with truckers, much like how Uber connects riders and drivers. We are a team of entrepreneurial individuals who are redefining the movement of things around the world. On the Uber Freight team, we fiercely believe that our dedication to transportation technologies will bring more harmonious, highly efficient, and increasingly safer transportation logistics to our roads. 

Our AI Execution team - is leveraging the best of AI technology to ensure smooth & predictable delivery of shipments for our customers. Logistics is a complex problem, where minutes and timing means millions for our customers. This team delivers AI first solutions to deliver real-world impact for tens of billions in freight each year. 

As the AI Scheduling & Facility Product Manager, you'll own facility data and scheduling for our shippers and carriers. You will go beyond the success of each shipment to drive network impact. You will architect the future of mult-modal scheduling - going beyond rules to deliver dynamic AI & ML systems that meet fleet and driver constraints, and nuanced requirements for all modes of transportation. You will build predictive solutions for the scheduling of today - think anticipating delays -  and the foundation for scheduling of the near future - think autonomous fleets.

What the candidate will do 

  • Product Vision and Strategy: Define a clear product vision and strategy for the team, identifying both short-term and long-term initiatives to create an effective product roadmap.
  • User-Centric Approach: Translate user needs into product requirements by deeply understanding user problems and business opportunities - formulating hypotheses, and articulating desired outcomes
  • Quality & Velocity: Leverage AI throughout research, prototyping & build to deliver high-quality product experiences.
  • Communication: Effectively communicate product plans, tradeoffs, and results to a diverse audience, including internal partner teams, 3rd party partners, executives, end-users, and external customers
  • Innovation: Lead the discovery, development, and adoption of innovative features and experiences improve outcomes for Uber Freight, our customers, and external partners
  • Cross-Functional Team Leadership: Collaborate with a strong team of engineers, designers, data scientists, and user researchers, setting clear team deliverables, defining the roadmap, and driving execution.
  • Cultivate Team Culture: Build and nurture a strong team culture centered around collaboration, execution, and delivering results.  

How the candidate will make immediate impact 

  • Define and execute strategies for Uber Freight's facility and scheduling products for all customer segments. 
  • Develop our data insights across facilities driving our unique value proposition. 
  • Build optimizations for individual shipments and beyond making scheduling a differentiator for Uber Freight's carrier and shipper network
  • Analyze market trends, competitor offerings, and monitor internal metrics to inform product decisions.
  • Obsess in the data and details of defects identified by users, operations teams, and intuition.
  • Ensure the higher ROI opportunities are prioritized, delivered iteratively, and evaluated regularly.
  • Uphold consistent communications with executive leaders to enforce growth strategy and impact quantification.

Basic Qualifications 

  • Minimum of 3+ years of Product Management experience developing and deploying world-class products that scale
  • Data-first approach to problem solving (know how to leverage SQL and AI research strategies to pull your own data and insights)
  • You aren't just an executor; you advocate for the right problems.
  • You take problems as opportunities; you lead through rallying, influence, and
  • You are well-versed in reinforcement learning; you have developed optimizations (ML models) or AI solutions 

Preferred Qualifications 

  • You have developed in the logistics industry or similar marketplace environments (think travel marketplace, booking)
  • Excellent communication and collaboration skills. Comfortability with presenting to, recommending changes, and pushing back on executive stakeholders.

Benefits & Compensation for U.S. Employees

Employees working more than 30 hours in the US at Uber Freight are eligible for benefits like a company sponsored health plan, dental and vision benefits, 401k match, financial and mental wellness benefits, parental leave, short- and long-term disability coverage, life insurance and more.  US based employees may also be eligible for a performance or sales incentive bonus program, participation in Uber Freight equity awards, and other types of compensation depending upon the role.

About Uber Freight 

Uber Freight helps companies move goods more reliably and efficiently. We bring together the technology, people, and transportation capacity they need, using realtime data from millions of shipments to guide smarter decisions. That helps customers spot issues early, avoid costly surprises, and deliver on time. Uber Freight works with 1 in 3 Fortune 500 shippers across North America and manages over $17B in freight. Learn more at www.uberfreight.com.

Candidate Privacy Notice

Uber Freight is committed to protecting the privacy of our candidates. We collect and process personal data in accordance with applicable data protection laws. For detailed information on how we handle candidate data, please review our Candidate Privacy Notice.

EEOC

Uber Freight is proud to be an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regards to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. 

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