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Reinforcement Learning Engineer Jobs in Chicago, IL

We are looking for someone with a passion for data, ML, and programming, who can build ML solutions ... Advanced knowledge in Reinforcement Learning or Meta Learning. * Software development experience is ...

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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 cities near Chicago, IL are hiring for Reinforcement Learning Engineer jobs? Cities near Chicago, IL with the most Reinforcement Learning Engineer job openings:
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.

AI & GenAI Data Scientist-Senior Associate

Pwc

Chicago, IL

$77K - $202K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 2 days ago

New


PwC rating

8.3

Company rating: 8.3 out of 10

Based on 76 frontline employees who took The Breakroom Quiz

25th of 72 rated business consultants


Job description

Industry/Sector

Not Applicable

Specialism

Data, Analytics & AI

Management Level

Senior Associate

Job Description & Summary

The Opportunity
As an AI & GenAI Data Scientist-Senior Associate, you will be at the forefront of transforming raw data into actionable insights, enabling informed decision-making and driving business growth. Within our Technology Consulting practice, you will apply data, algorithms, and software engineering to build and deploy software and platform systems that create Artificial Intelligence and Machine Learning-based solutions at scale. Your work will involve designing AI systems, data wrangling, and software implementation to enable the AI models to be useful and scalable.
As a Senior Associate, you will focus on building meaningful client connections and learning how to manage and inspire others. You will navigate increasingly complex situations, growing your personal brand and deepening your technical skills. You are expected to anticipate the needs of your teams and clients, delivering quality solutions. Embracing increased ambiguity, you will be comfortable when the path forward isn't clear, using these moments as opportunities to grow.
In this role, you will leverage advanced technologies and techniques to design and develop robust data solutions for clients. Your contributions will be crucial in transforming data into insights, driving business growth, and enabling informed decision-making.
Responsibilities
- Designing and implementing AI systems to transform raw data into actionable insights
- Developing and deploying scalable AI and Machine Learning solutions using advanced technologies
- Collaborating with clients to understand their data needs and deliver tailored solutions
- Utilizing programming languages such as Python and C++ to build robust data models
- Managing data pipelines and confirming data quality and integration across platforms
- Applying machine learning libraries like TensorFlow and Scikit-Learn to enhance model performance
- Conducting complex data analysis to inform strategic decision-making
- Leveraging natural language processing and text analytics for innovative AI applications
- Building and maintaining data infrastructure to support AI-driven automation
- Mentoring junior team members and fostering a collaborative work environment
What You Must Have
- At least a Bachelor's degree
- At least 2 years of experience
What Sets You Apart
- Preference for at least one of the following fields of study: Management Information Systems, Computer and Information Science, Systems Engineering, Mathematics, Engineering, Electrical Engineering, Chemical Engineering, Industrial Engineering, Mathematics, Statistics, or Mathematical Statistics, Data Processing/Analytics/Science, Artificial Intelligence and Robotics
- At least one of the following: Certifications aligned to data engineering, machine learning, and cloud platforms, including AWS, Google Cloud, Microsoft Azure, Databricks, Snowflake, or related data and AI credentials
- Demonstrating proficiency in AI implementation and machine learning libraries
- Utilizing Python for complex data analysis and modeling
- Excelling in neural network design and reinforcement learning agents
- Applying natural language processing techniques for text analytics
- Leveraging TensorFlow and Scikit-Learn for deep learning projects

Travel Requirements

Up to 80%

Job Posting End Date

The salary range for this position is: $77,000 - $202,000. Actual compensation within the range will be dependent upon the individual's skills, experience, qualifications and location, and applicable employment laws. All hired individuals are eligible for an annual discretionary bonus. PwC offers a wide range of benefits, including medical, dental, vision, 401k, holiday pay, vacation, personal and family sick leave, and more. To view our benefits at a glance, please visit the following link: https://pwc.to/benefits-at-a-glanceAs PwC is anequal opportunity employer, all qualified applicants will receive consideration for employment at PwC without regard to race; color; religion; national origin; sex (including pregnancy, sexual orientation, and gender identity); age; disability; genetic information (including family medical history); veteran, marital, or citizenship status; or, any other status protected by law.PwC does not intend to hire experienced or entry level job seekers who will need, now or in the future, PwC sponsorship through the H-1B lottery, except as set forth within the following policy: https://pwc.to/H-1B-Lottery-Policy.Learn more about how we work: https://pwc.to/how-we-workFor only those qualified applicants that are impacted by the Los Angeles County Fair Chance Ordinance for Employers, the Los Angeles' Fair Chance Initiative for Hiring Ordinance, the San Francisco Fair Chance Ordinance, San Diego County Fair Chance Ordinance, and the California Fair Chance Act, where applicable, arrest or conviction records will be considered for Employment in accordance with these laws. At PwC, we recognize that conviction records may have a direct, adverse, and negative relationship to responsibilities such as accessing sensitive company or customer information, handling proprietary assets, or collaborating closely with team members. We evaluate these factors thoughtfully to establish a secure and trusted workplace for all.Applications will be accepted until the position is filled or the posting is removed, unless otherwise set forth on the following webpage. Please visit this link for information about anticipated application deadlines: https://pwc.to/us-application-deadlines

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