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Reinforcement Learning Robotics Jobs (NOW HIRING)

Dexmate is building the foundation for physical AI -- a unified platform that combines high-quality robotic hardware with a universal Physical AI OS. They are seeking Reinforcement Learning experts ...

Robotics & AI Research Engineer Description Auzmor is redefining workforce training by seamlessly ... You will develop state-of-the-art machine learning models, reinforcement learning algorithms, and ...

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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.

More about Reinforcement Learning Robotics jobs
What cities are hiring for Reinforcement Learning Robotics jobs? Cities with the most Reinforcement Learning Robotics job openings:
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Infographic showing various Reinforcement Learning Robotics job openings in the United States as of June 2026, with employment types broken down into 98% Full Time, 1% Temporary, and 1% Contract. Highlights an 92% Physical, 1% Hybrid, and 7% Remote job distribution.
Intern - Reinforcement Learning Engineer

Intern - Reinforcement Learning Engineer

Ghost Robotics

Philadelphia, PA โ€ข On-site

$30 - $45/hr

Other

Posted 23 days ago


Job description

Description

Ghost Robotics is the industry leader in legged robotic systems that not only help our customers solve complex operational, national security, and technical challenges to save lives, reduce harm and improve outcomes.ย ย 


We are looking for a part-time Reinforcement Learning Intern to work with the Chief Science Officer to develop reinforcement learning algorithms for quadrupedal robot self-righting.ย 


Key Duties:

  • Develop infrastructure - scripts for training and evaluating algorithm progress
  • Use mjlab for training in simulation, with domain randomization for zero-shot sim2sim and sim2real transfer
  • Hands-on testing on the physical robot
  • Reward tuning for desirable performance

Requirements

Recommended Qualifications:

  • Holds Bachelor's degree in Computer Engineering, Software Engineering, or a related field
  • Currently pursuing Masters degree in Computer Engineering, Software Engineering, or a related field
  • Expertise in reinforcement learning algorithms like PPO, TRPO
  • Experience with weights & biases dashboard setup
  • Python programming experience
  • Mjlab or Isaac sim experience
  • Optional but highly desirable: taken ESE 6510 Physical Intelligence course at Penn (or equivalent)

Locationย ย 

Philadelphia, PA (no remote candidates considered at this time).ย ย 


Schedule and Committment

Flexible, part-time schedule, 20 - 30 hours per week. ย Able to commit to three (3) month minimum project, with option to extend following evaluation.


Travelย ย 

No Travel Required.ย ย 


Compensationย 

Competitive base $30 - $45 per hour.


Background Checkย ย 

Clear standard background checks, pre-hire, post hire and anytime during employment as required.ย ย 


Residency Requirementsย 

Employment Authorization Required.ย 


Intellectual Property

Note: An IP agreement needs to be signed for this project, and any public release of project outputs requires prior company approval.


Physical Requirementsย 

  • Prolonged periods of standing, sitting at a desk and working on a computer.ย ย 
  • Must be able to lift 20 pounds. Assistive equipment available.
    ย