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Reinforcement Learning Robotics Jobs in Detroit, MI

ALTEN Technology USA

Practice Manager - AI & Data

Troy, MI · On-site

$160K - $190K/yr

... devices, robotics, automotive, commercial vehicles, EVs, rail, and more. As part of the global ... Machine Learning & Deep Learning (supervised, unsupervised, reinforcement learning) * Support ...

Mariana Minerals

Sr. Data Engineer

Ann Arbor, MI · On-site

$140K - $200K/yr

Our internal platform, PlantOS, uses the same reinforcement learning toolkits that power self-driving vehicles and humanoid robots-but applied to autonomous, short-interval control of mineral ...

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Reinforcement Learning Robotics information

What are some common challenges faced when implementing reinforcement learning algorithms in robotics projects?

One common challenge in this role is bridging the gap between simulation and real-world environments, as algorithms that perform well in simulation may not translate directly to physical robots due to unpredictable variables and hardware limitations. Additionally, ensuring the safety and stability of the robot during training is crucial, since trial-and-error learning can sometimes result in unintended behaviors or hardware damage. Collaboration with hardware engineers and domain experts is often necessary to fine-tune models, interpret results, and iterate on solutions. Overcoming these challenges requires patience, adaptability, and strong communication skills within a multidisciplinary team.

What are the key skills and qualifications needed to thrive as a reinforcement learning robotics engineer, and why are they important?

To thrive as a Reinforcement Learning Robotics Engineer, you need a strong background in robotics, machine learning, and programming, typically supported by a degree in computer science, engineering, or a related field. Expertise with frameworks like TensorFlow or PyTorch, experience with simulation environments (such as Gazebo or ROS), and familiarity with reinforcement learning algorithms are essential. Strong problem-solving skills, creativity, and effective communication set standout professionals apart in this rapidly evolving field. These skills enable engineers to develop intelligent robotic systems that adapt and learn efficiently, driving innovation and practical deployment in real-world environments.

What is reinforcement learning in robotics?

Reinforcement learning in robotics refers to a type of machine learning where robots learn to perform tasks through trial and error, receiving feedback from their actions in the form of rewards or penalties. This approach allows robots to autonomously develop complex behaviors by interacting with their environment, rather than relying solely on pre-programmed instructions. Reinforcement learning is especially useful for tasks that are difficult to model explicitly, such as walking, grasping, or navigation. Over time, the robot improves its performance by maximizing the cumulative reward, leading to more efficient and adaptive behaviors.

What is the difference between Reinforcement Learning Robotics vs Machine Learning Engineer?

AspectReinforcement Learning RoboticsMachine Learning Engineer
Required CredentialsDegree in Robotics, Computer Science, or related fields; knowledge of reinforcement learningDegree in Computer Science, Data Science, or related fields; expertise in machine learning algorithms
Work EnvironmentRobotics labs, manufacturing, autonomous systemsTech companies, data-driven projects, software development
Industry UsageAutonomous robots, industrial automation, researchData analysis, predictive modeling, AI applications

Reinforcement Learning Robotics focuses on applying reinforcement learning techniques to control and optimize robotic systems, often in physical environments. Machine Learning Engineers develop algorithms for a broad range of applications, including data analysis and predictive modeling. While both roles require knowledge of machine learning, Reinforcement Learning Robotics emphasizes robotics and real-world interaction, whereas Machine Learning Engineers work across various industries with software-based solutions.

What are popular job titles related to Reinforcement Learning Robotics jobs in Detroit, MI? For Reinforcement Learning Robotics jobs in Detroit, MI, the most frequently searched job titles are:
What job categories do people searching Reinforcement Learning Robotics jobs in Detroit, MI look for? The top searched job categories for Reinforcement Learning Robotics jobs in Detroit, MI are:
Reinforcement Learning Robotics jobs near you
Infographic showing various Reinforcement Learning Robotics job openings in Detroit, MI as of June 2026, with employment types broken down into 97% Full Time, 1% Part Time, 1% Temporary, and 1% Contract. Highlights an 92% Physical, 1% Hybrid, and 7% Remote job distribution.

Contract Engineer, Advanced Engineering & Research

Isuzu Motors America LLC

Plymouth, MI • On-site

$44 - $48/hr

Other

Re-posted 16 days ago

Job description

Isuzu Technical Center of America is seeking a Contract Engineer, Advanced Engineering & Research to join its operations in Plymouth, MI. The selected candidate will be placed with a preferred agency for employment.
JOB SUMMARY
Supports verification and validation of Level 4 autonomous driving technologies and robotic systems using state-of-the-art approaches and methodologies such as generative AI, vision-language-action mdoels and world models. Works closely with Isuzu US and Japan teams, well-known external autonomous driving partner companies, and reputed research institutes on the validation and deployment of autonomous systems. Works at the intersection of vehicle engineering and cutting-edge autonomous technology within a collaborative and passionate environment. Works with direction from manager and guidance from more senior staff.
% of time spenton each activity
PRINCIPAL DUTIES & RESPONSIBILITIES
30%
1.
Collaborates with global ISUZU teams and research parternership to deploy generative AI and state-of-the-art methods to validate L4 autonomous driving technologies and robotic systems.
20%
2.
Analyzes open source and on-road driving data and use data driven insights to enhance simulations.
20%
3.
Supports simulation of edge case scenarios to test and validate AV systems.
20%
4.
Participates in cross-functional discussions and contributes ideas toward improving safety and reliability of AV systems.
10%
5.
Prepares and communicates findings and technical updates to internal and external research teams across the U.S. and Japan.
6.
Performs miscellaneous job-related duties as assigned.
ORGANIZATIONAL RELATIONSHIPS
  • Reports to: Manager, Autonomous Driving & MBD

EDUCATION, EXPERIENCE & TRAINING
  • Master's degree in Computer Science, Electrical Engineering, Robotics, Data Science or related field
  • Minimum one (1) year of prior internship or project experience in AI, VLM, world models, data analysis, programming, or automotive systems

KNOWLEDGE
  • Foundational understanding of data analysis, statistics, or simulation
  • Basic knowledge of autonomous driving or vehicle safety systems is a plus

SKILLS & ABILITIES
  • Strong analytical and problem-solving skills
  • Strong in Python, C++, or Java
  • Proficient with simulation and machine learning / reinforcement learning tools
  • Effective communication and interpersonal skills
  • Ability to work independently and collaboratively within a team

PHYSICAL STANDARDS
The employee must be able to access, enter, and retrieve data using a computer. This is primarily a sedentary position in a controlled office environment which requires only occasional reaching, stooping, and lifting of office files, reports or records, typically weighing 5 lbs. or less. Requires occasional light lifting (5-25 lbs) and on rare occasions, heavy lifting (60 lbs). Must be able on rare occasions to bend, crawl, climb, crouch, kneel and reach above shoulder level in the performance of job duties. Must be able to work in hot and cold weather extremes.
#ITCA

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