ZipRecruiter

Log In

1

Reinforcement Learning Robotics Jobs (NOW HIRING)

Codertal

Reinforcement Learning Engineer

Union, NJ · Remote

Bachelor's or Master's degree in AI, ML, Robotics, or related field. Intermediate to high level of ... of Reinforcement Learning, we'd love to hear from you! Apply Now Name Phone Email Rate per day ...

Auzmor

Robotics & AI Research Engineer

Des Moines, IA · On-site

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 ...

Meta

AI Research Scientist, Robotics

Menlo Park, CA

$184K/yr

Experience with any of the following research areas: robotics, motion planning, embodied AI, human-robot interaction, sim-to-real transfer, learning from demonstration, reinforcement learning ...

Meta

AI Research Scientist, Robotics

Menlo Park, CA · On-site

$184K - $257K/yr

... learning, learning from demonstration, reinforcement learning, action-conditioned world models, perception, representation learning, robot control, navigation, mobile manipulation, dexterous ...

Apptronik

Senior Reinforcement Learning Engineer

Austin, TX · On-site

$103K - $142K/yr

Our flagship humanoid robot, Apollo, is built to collaborate thoughtfully with people, starting ... JOB SUMMARY The Senior Reinforcement Learning Engineer is a key, hands-on role focused on achieving ...

Horizon Robotics

Research Scientist

Cupertino, CA · Hybrid

$150K - $300K/yr

We are looking for someone with expertise in and enthusiasm for machine learning research, especially in Robotics, Embodied AI, Reinforcement learning (RL) , etc. As a Research Scientist in the team ...

next page

Showing results 1-20

People also search for

All JobsReinforcement Learning Robotics Jobs

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:
What states have the most Reinforcement Learning Robotics jobs? States with the most job openings for Reinforcement Learning Robotics jobs include:
What job categories do people searching Reinforcement Learning Robotics jobs look for? The top searched job categories for Reinforcement Learning Robotics jobs are:
Reinforcement Learning Robotics jobs near you
Infographic showing various Reinforcement Learning Robotics job openings in the United States as of May 2026, with employment types broken down into 1% As Needed, 98% Full Time, and 1% Temporary. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

Reinforcement Learning Engineering Intern

Persona AI

Pensacola, FL • On-site

$14.25 - $19/hr

Internship

Posted 16 days ago

Job description

Persona AI is developing and commercializing rugged, multi-purpose humanoid robots that perform real work. Persona's founding team has a decades-long history in humanoid robotics, bionics, and product development delivering robust hardware that has touched the stars, worked miles below the surface of the ocean, and even roamed Disney Parks. Our mission is focused squarely on shipping beautiful, reliable products at massive scale, while building a customer-focused team to achieve these aims.
Reinforcement Learning Engineering Intern
Location: Downtown Pensacola, FL
Type: Full-time Internship, 40 hours/week
About the Internship
The Reinforcement Learning Engineering Internship is an opportunity for Bachelors and Masters candidate students to join and contribute to the Persona team as we develop our industrial humanoids. Our objective is to provide each intern with a positive learning environment, hands-on experience with humanoids, and ownership over their own project direction. We are looking for students with an excitement for learning, technical excellence, and creative problem-solving skills.
Each intern will have a designated mentor to provide guidance and assistance in developing and making progress towards a target goal. We have a strong bias for projects that lead to software, controls, or policies deployed on our hardware and extending the capabilities of our systems. Projects will be jointly planned by the intern and their mentor to build on the intern's background, extend their experience to new areas of interest, and fit into the broader goals of the Persona reinforcement learning team.
Role Description
For this role, the specific tasks will be defined prior to the start date by the mentor and the intern based on their experience, proficiency, and personal interests. The scope may also be adjusted to fit the project within the intern's time-frame. We encourage interns to share their interests even if they may be entirely different from their technical background. Some example general tasks that may be a part of any project are described below:
  • Develop new simulation training environments
  • Design new behaviors or extend capabilities for the Persona robots
  • Deploy to hardware, log data, and analyze results
  • Create or implement new algorithms for modeling, training, sensing, or deployment
  • Characterize hardware sensors, actuators, and general robot parameters
Qualifications
  • Current Undergraduate or Masters student
  • Software proficiency in Python, C/C++, Java, or Rust
  • Experience with basic machine learning concepts
Bonus Experience
  • Worked with Pytorch or similar
  • Physics simulator experience such as IsaacLab/IsaacSim, Mujoco, or similar
  • Deployed controls software to robot hardware
  • Trained policies with reinforcement learning
  • Worked with motion diffusion models or VLAs
  • Experience with character animation
  • Worked on vision or localization
Open Technical Areas
  • Perception
  • Locomotion
  • Manipulation
  • Motion Planning
  • Imitation Learning
  • Motion Retargeting
  • Sim-to-Real Modeling
Application Timeline
We are accepting applications on a rolling basis. We will interview and make offers for upcoming intern cohorts until we fill all openings. We will close the application process for an upcoming cohort approximately 3 months before the start of the cohort and recommend applying approximately 6 months in advance.
Note: we are no longer accepting applications for Summer 2026.
The interview process we are currently following involves two interviews. First, a phone pre-screen with a member of our staff. Second, a presentation and discussion interview with one to two of our engineers. The presentation is meant to be informal and give an opportunity for you to share your background, experiences, and interests. We like the chance to see pictures and videos of your projects and hear what part of robotics excites you most! We will also give an overview of the work we are doing here at Persona AI and leave time for you to ask us questions.
We aim to get back to you as soon as we can but it may take a few weeks, especially in between cohorts. Please know we are working on it and will get back to every application!
Why join Persona AI?
  • You'll shape technology that's redefining the possibilities of robotics and human interaction.
  • Work alongside passionate teammates who value diversity, creativity, and continuous learning.
  • Enjoy full access to advanced prototyping tools, labs, and the freedom to experiment and innovate.
  • We offer competitive compensation, excellent benefits, flexible work environment, and equity opportunities.
Persona AI embraces diversity and equal opportunity in a serious way. We are committed to building a team that represents a variety of backgrounds, perspectives, and skills. We believe the more inclusive we are, the better our work will be.

Apply