1

Reinforcement Learning Engineer Jobs in Milwaukee, WI

Partners cross-functionally with brand, engineering, operations, finance, and insights teams to ... Leads innovation-process adoption by delivering training, onboarding, and reinforcement to build ...

Partners cross-functionally with brand, engineering, operations, finance, and insights teams to ... Leads innovation-process adoption by delivering training, onboarding, and reinforcement to build ...

Reinforcement Learning Engineer information

See Milwaukee, WI salary details

$37.4K

$114.2K

$188.7K

How much do reinforcement learning engineer jobs pay per year?

As of Jul 30, 2026, the average yearly pay for reinforcement learning engineer in Milwaukee, WI is $114,155.00, according to ZipRecruiter salary data. Most workers in this role earn between $81,800.00 and $149,300.00 per year, depending on experience, location, and employer.

What are Reinforcement Learning Engineers?

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 Milwaukee, WI? For Reinforcement Learning Engineer jobs in Milwaukee, WI, the most frequently searched job titles are:
What job categories do people searching Reinforcement Learning Engineer jobs in Milwaukee, WI look for? The top searched job categories for Reinforcement Learning Engineer jobs in Milwaukee, WI are:

Senior Software and Algorithm Engineer

Johnson Controls

Milwaukee, WI • On-site, Remote

$120K - $159K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

This job post has expired today. Applications are no longer accepted.


Johnson Controls rating

8.0

Company rating: 8.0 out of 10

Based on 402 frontline employees who took The Breakroom Quiz

133rd of 536 rated manufacturers


Job description

Build your best future with the Johnson Controls team!

Who we are:

Johnson Controls is global leader in smart, healthy, and sustainable buildings. Our mission is to reimagine the performance of buildings to serve people, places, and the planet. Join a winning team that enables you to build your best future! Our teams are uniquely positioned to support a multitude of industries across the globe. You will have the opportunity to develop yourself through meaningful work projects and learning opportunities. We strive to provide our employees with an experience focused on supporting their physical, financial, and emotional wellbeing. Become a member of the Johnson Controls family and thrive in an empowering company culture where your voice and ideas will be heard - your next great opportunity is just a few clicks away!

About Central Utility Plant Optimization

Central plants are the biggest contributor to occupant comfort, the biggest supplier of energy-and the biggest consumer of energy. Building managers can keep it running at optimum efficiency with the next generation of plant optimization software from Johnson Controls. We build on our innovative OpenBlue digital platform to connect systems and data for intelligent, automated decision-making. Our Enterprise Manager Central Utility Plant Optimization (CUPO) solution monitors thousands of variables, gathering data every 15 minutes from your connected equipment and from external sources such as weather forecasts and utility rates. CUPO automatically generates and implements optimization decisions, controlling many brands of equipment and plant types. Customers see rapid ROI, reduced costs, increased reliability, and advancement of sustainability goals.

What We Offer:

  • Competitive salary

  • Paid vacation/holidays/sick time

  • Comprehensive benefits package including 401K, medical, dental, and vision care.

  • On-the-job/cross-training opportunities

  • Encouraging and collaborative team environment

  • Dedication to safety through our Zero Harm policy

What you will do:

As a member of the OpenBlue AI team, the Senior Algorithm Engineer leads development and maintenance of the numerical algorithms that underpin the CUPO solution. You will improve existing algorithms to cover new equipment types and configurations or enhance optimization performance. The position will also work closely with site and modeling teams to understand reported issues, identify fixes, and resolve bugs in the algorithm code. Finally, you will contribute to development of other autonomous buildings capabilities, including optimization of airside equipment. We prefer to have this individual reside in Eastern time zone, but this is a remote opportunity.

Successful candidates will bring a strong engineering foundation and hands-on experience with numerical software development. Proficiency in MATLAB is essential, with working knowledge of Python also required. Candidates must be comfortable with reading, understanding, and debugging code written by others. Familiarity with HVAC equipment (particularly chillers), thermodynamic systems including mass/energy balances, and mathematical optimization is highly valued

How you will do it:

  • Develop and maintain MATLAB and Python code to implement new CUPO algorithm features and support new equipment configurations

  • Debug and resolve algorithm issues reported from live sites, working closely with field and modeling teams

  • Review peer code and develop test cases to ensure algorithm correctness and quality

  • Collaborate with product management to prioritize and plan development tasks, leveraging JIRA to track work and open issues

  • Partner with site teams to diagnose and resolve reported issues

  • Work independently to identify root causes of bugs and plan fixes

  • Contribute to autonomous buildings initiatives through Python-based optimization modules

  • Read and write Python code for other autonomous buildings and optimization capabilities

What you will need:

Required

  • Bachelor's degree in mechanical, electrical, chemical, or other engineering field

  • Familiarity with system-of-equations solvers for interconnected HVAC plant equipment

  • Proficiency in MATLAB for numerical algorithm development and debugging.

  • Experience with Python and scientific computing libraries (NumPy, SciPy) for data processing and algorithm implementation

  • Familiarity with optimal-control strategies (e.g., dynamic programming, model-predictive control, reinforcement learning)

Preferred

  • Graduate degree in Mechanical Engineering, Systems Engineering, or a related field with a focus on building energy systems, thermodynamics, or optimization

  • Eight years of experience in applied engineering

  • Excellent verbal and written communication skills

  • Experience with Python and data-science packages (Pandas, Scikit-Learn, etc.)

  • Experience reading and writing C# code

  • Experience modeling HVAC equipment (chillers, cooling towers, AHUs, etc.)

  • Familiarity with mass and energy balances and thermodynamics

  • Familiarity with numerical optimization (e.g., mixed-integer linear/nonlinear programming)

  • Proficiency in optimal-control strategies (e.g., dynamic programming, model-predictive control, reinforcement learning)

  • Experience writing and debugging numerical simulations

  • Experience with JIRA

SALARY RANGE: $89,000 - $149,000 (Salary to be determined by the education, experience, knowledge, skills, and abilities of the applicant, internal equity, and alignment with market data.) This position includes a competitive benefits package. The posted salary range reflects the target compensation for this role. However, we recognize that exceptional candidates may bring unique skills and experiences that exceed the typical profile. If you believe your background warrants consideration beyond the stated range, we encourage you to apply. To support an efficient and fair hiring process, we may use technology assisted tools, including artificial intelligence (AI), to help identify and evaluate candidates. All hiring decisions are ultimately made by human reviewers. For details, please visit the About Us tab on the Johnson Controls Careers site at https://jobs.johnsoncontrols.com/about-us

Johnson Controls International plc. is an equal employment opportunity and affirmative action employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, age, protected veteran status, genetic information, sexual orientation, gender identity, status as a qualified individual with a disability or any other characteristic protected by law. To view more information about your equal opportunity and non-discrimination rights as a candidate, visit EEO is the Law. If you are an individual with a disability and you require an accommodation during the application process, please visit here.


What Johnson Controls employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


Johnson Controls logo

About Johnson Controls

Sourced by ZipRecruiter

Johnson Controls is a world leader in smart buildings, creating safe, healthy and sustainable spaces. For nearly 140 years, we’ve made buildings better and now we’re transforming them again with our award-winning digital technologies and services. We’re using artificial intelligence and data driven solutions to give you deeper insight into your building’s health, sustainability and performance. It’s changing the way we design, operate and maintain indoor environments and driving to a new era of autonomous buildings. We deliver the blueprint of the future for industries such as healthcare, schools, data centers, airports, stadiums, hotels, manufacturing and beyond through OpenBlue, our comprehensive suite of connected solutions. Johnson Controls offers the world’s largest portfolio of building technology, software and services. Supported by a team of more than 100,000 dedicated employees working across 150 countries, we’re helping customers achieve their sustainability goals and power their mission.

Industry

Machinery manufacturing, water transportation, public safety statistics centers and offices and manufacturing

Company size

10,000+ Employees

Headquarters location

Milwaukee, WI, US