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Reinforcement Learning Engineer Jobs in Michigan

Eccalon LLC

AI Expert Robotics - onsite

Detroit, MI · On-site

Strong programming experience in Python and/or C++ * Hands-on experience with machine learning ... Experience with computer vision, deep learning, or reinforcement learning * Familiarity with ...

Megan soft Inc

Senior AI/ML Engineer

Dearborn Heights, MI · On-site

$96K - $132K/yr

... automation, reinforcement learning, virtual assistants and specialized programming * Research and optimize AI technologies to enhance efficiency and accuracy of data analysis and create more ...

University of Michigan

RESEARCH FELLOW

Ann Arbor, MI · On-site

... perception, reinforcement learning, and neural plasticity. We study questions at a variety of ... Detail-oriented, quantitative mindset and experience with scientific programming (Matlab, python ...

KLA Corporation

Senior AI Ops Engineer

Ann Arbor, MI · On-site

$102K - $140K/yr

... and Reinforcement Learning with Human Feedback (RLHF). We encourage you to apply if you're a systems-minded engineer who loves turning research workflows into reliable production-grade pipelines ...

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Reinforcement Learning Engineer information

See Michigan salary details

$33.1K

$101K

$166.9K

How much do reinforcement learning engineer jobs pay per year?

As of Jun 18, 2026, the average yearly pay for reinforcement learning engineer in Michigan is $100,987.00, according to ZipRecruiter salary data. Most workers in this role earn between $72,300.00 and $132,000.00 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 Michigan? For Reinforcement Learning Engineer jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Reinforcement Learning Engineer jobs in Michigan look for? The top searched job categories for Reinforcement Learning Engineer jobs in Michigan are:
What cities in Michigan are hiring for Reinforcement Learning Engineer jobs? Cities in Michigan with the most Reinforcement Learning Engineer job openings:
Reinforcement Learning Engineer jobs near you
Infographic showing various Reinforcement Learning Engineer job openings in Michigan as of June 2026, with employment types broken down into 99% Full Time, and 1% Contract. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $100,987 per year, or $48.6 per hour.

Robotics Engineer

Tata Consultancy Service Limited

Troy, MI • On-site

$100K - $130K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 13 days ago

Job description

Must Have Technical/Functional Skills
  • Strong ROS/ROS2 experience
  • Proficiency in C++ and/or Python
  • Experience with SLAM, navigation stack, and sensor fusion
  • Hands-on hardware integration experience
  • Debugging in real-world environments
  • Reinforcement learning
  • Multi-robot systems (Swarm cases)
  • Cloud integration (MQTT, telemetry)
  • Manufacturing or warehouse automation exposure

Roles & Responsibilities
Robotics Engineers with strong hands-on expertise in ROS/ROS2 to build and deploy real-world Physical AI solutions in manufacturing and enterprise environments. This is a build-and-deploy role, not research-only.
Responsibilities:
  • Develop robotic applications using ROS/ROS2
  • Implement navigation, SLAM, perception, and autonomy
  • Integrate sensors (LiDAR, IMU, depth cameras) and actuators
  • Work with robotic arms, mobile robots, AGVs, or quadrupeds
  • Deploy solutions on edge devices (Jetson or similar)
  • Support simulation (Gazebo/Isaac)
  • Collaborate with AI and platform teams for connected robotics use cases

Generic Managerial Skills, If any
  • Experts who have deployed real robots (not just simulations)
  • Strong system thinking and problem-solving mindset
  • Ability to operate in fast-paced innovation environments

Base Salary Range : $100,000 to $130,000 Per Annum
TCS Employee Benefits Summary:
Discretionary Annual Incentive.
Comprehensive Medical Coverage: Medical & Health, Dental & Vision, Disability Planning & Insurance, Pet Insurance Plans.
Family Support: Maternal & Parental Leaves.
Insurance Options: Auto & Home Insurance, Identity Theft Protection.
Convenience & Professional Growth: Commuter Benefits & Certification & Training Reimbursement.
Time Off: Vacation, Time Off, Sick Leave & Holidays.
Legal & Financial Assistance: Legal Assistance, 401K Plan, Performance Bonus, College Fund, Student Loan Refinancing.
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