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Reinforcement Learning Engineer Jobs in Dolton, IL

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 ...

New

JP Morgan Chase

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 ...

New

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

Reinforcement Learning Engineer information

See Dolton, IL salary details

$36.3K

$110.7K

$182.9K

How much do reinforcement learning engineer jobs pay per year?

As of Sep 3, 2026, the average yearly pay for reinforcement learning engineer in Dolton, IL is $110,665.00, according to ZipRecruiter salary data. Most workers in this role earn between $79,300.00 and $144,700.00 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 cities near Dolton, IL are hiring for Reinforcement Learning Engineer jobs?

Cities near Dolton, IL with the most Reinforcement Learning Engineer job openings:

Reinforcement Learning Engineer jobs near you
Infographic showing various Reinforcement Learning Engineer job openings in Dolton, IL as of August 2026, with employment types broken down into 85% Full Time, and 15% Contract. Highlights an 84% In-person, and 16% Remote job distribution, with an average salary of $110,665 per year, or $53.2 per hour.

Applied AI/ML - Vice President

JPMorgan Chase & Co

Chicago, IL • On-site

Full-time

Medical, Retirement

Posted 2 days ago

New

JPMorgan Chase & Co. rating

8.0

Company rating: 8.0 out of 10

Based on 499 frontline employees who took The Breakroom Quiz

72nd of 174 rated banks

Job description

Are you looking for an exciting opportunity to solve exciting business problems? Our Technology team builds innovative products, services, applications to support various business functions, workflows of Wholesale Lending Services.

As an Applied AI/ML Vice President within the Corporate and Investment Bank (CIB) Technology team at JPMorganChase, you will lead the analysis of complex business problems, design and experiment with state-of-the-art models, and develop robust machine learning and deep learning solutions. You will apply your expertise in machine learning toolkits and algorithms to identify, build, and deliver fit-for-purpose solutions that promote measurable business impact. As a part of an innovative, cross-functional team, you will collaborate closely with product owners, data engineers, and software engineers to architect and implement new systems and capabilities. This role is ideal for someone with a strong passion for data, machine learning, and software development, who can navigate and interpret the data landscape of large, complex organizations to unlock actionable insights and scalable AI solutions.

Job Responsibilities

  • Lead programs and provide directions to successfully implement the large AI/ML initiatives and assist product leadership in defining the problem statements, execution roadmap
  • Develop state-of-the art machine learning models to solve real-world problems and apply it to tasks such as NLP, personalization, or recommendation systems.
  • Collaborate with business, operations, and other technology colleagues to understand AI needs and devise possible solutions.
  • Develop end-to-end ML/AutoML/AutoNLP pipelines and operationalize the end-to-end orchestration of the ML models to support the various use cases like Document Q&A, Search, Information Retrieval, classification, personalization, etc.
  • Build both batch and real-time model prediction pipelines with existing application and front-end integrations.
  • Collaborate to develop large-scale data modeling experiments, explain complex concepts to senior leaders and stakeholders.
  • Collaborate with multiple partner teams such as Business, Technology, Product Management, Legal, Compliance, Strategy and Business Management to deploy solutions into production.
  • Work with Product Owners and Software Engineers to productionize the models and Partners closely with business partners to identify impactful projects, influence key decisions with data, and ensure client satisfaction and deliver regular team updates and maintain full transparency into the team's priorities, progress, and deliverables across stakeholders.
  • Champion a culture of recognition by actively celebrating individual and team accomplishments, reinforcing a positive and high-performing team environment.

Required qualifications, capabilities, and skills

  • Master's or Ph.D. in Computer Science, Data Science, Statistics, Mathematical Sciences or Machine Learning with strong background in Mathematics and Statistics.
  • 7+ years' experience in applying data science, ML techniques to solve business problems and one of the programming languages like Python, Java, C/C++, etc.
  • Experience with LLMs and Prompt Engineering techniques.
  • 1+ year of experience working with Gen AI solutions / LLMs such as  GPT, Claude, Llama etc.
  • Solid background in NLP, Generative AI and hands-on experience and solid understanding of Machine Learning and Deep Learning methods and familiar with large language models
  • Extensive experience with Machine Learning and Deep Learning toolkits (e.g.: Transformers, Hugging Face, TensorFlow, PyTorch, NumPy, Scikit-Learn, Pandas)
  • Ability to design experiments and training frameworks, and to outline and evaluate intrinsic and extrinsic metrics for model performance aligned with business goals.
  • Experience with Big Data and scalable model training and solid written and spoken communication to effectively communicate technical concepts and results to both technical and business audiences.
  • Experience with building and deploying ML models on AWS esp. using AWS tools like Sagemaker, EC2, Glue, etc.
  • Knowledge of the Active Learning, Agent/Multi Agent Learning, Learning from Supervision/Feedback, etc. Scientific thinking with the ability to invent and to work both independently and in highly collaborative team environments.
  • Ability to work on tasks and projects through to completion with limited supervision. Passion for detail and follow through. Excellent communication skills and team player

Preferred qualifications, capabilities and skills

  • Published research in areas of Machine Learning, Deep Learning or Reinforcement Learning at a major conference or journals
  • Experience with A/B experimentation and data/metric-driven product development
  • Ability to develop and debug production-quality code and familiarity with continuous integration models and unit test development
JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world's most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.

We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process. 

We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.

JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans

J.P. Morgan's Commercial & Investment Bank is a global leader across banking, markets, securities services and payments. Corporations, governments and institutions throughout the world entrust us with their business in more than 100 countries. The Commercial & Investment Bank provides strategic advice, raises capital, manages risk and extends liquidity in markets around the world. 

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