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Robotics Manipulation Reinforcement Learning Jobs

Meta

Research Engineer Robotics (Systems)

Redmond, WA

$183K/yr

Deploy and iterate on learned control policies (imitation learning, MPC, reinforcement learning ... Experience in dexterous manipulation, learned robotic policy deployment, or control theory applied ...

Skild AI

Robotics Engineer, Manipulation

San Mateo, CA

$100K - $300K/yr

We believe massive scale through data-driven machine learning is the key to unlocking these ... Help design algorithms, models, and techniques for various robotic manipulation tasks. * Design ...

NIO

AI Robotics Researcher

San Jose, CA · On-site

$163K - $212K/yr

Deep understanding of robot learning , reinforcement learning , imitation learning , world modeling , or differentiable physics simulation . * Hands-on experience with robotic manipulation , grasp ...

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Robotics Manipulation Reinforcement Learning information

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$84K

$96K

$116.5K

How much do robotics manipulation reinforcement learning jobs pay per year?

As of Jun 23, 2026, the average yearly pay for robotics manipulation reinforcement learning in the United States is $96,000.00, according to ZipRecruiter salary data. Most workers in this role earn between $90,000.00 and $102,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Robotics Manipulation Reinforcement Learning Engineer, and why are they important?

To thrive as a Robotics Manipulation Reinforcement Learning Engineer, you need a solid background in robotics, machine learning (especially reinforcement learning), computer science, and typically an advanced degree such as a Master's or PhD. Experience with programming languages like Python or C++, frameworks such as TensorFlow or PyTorch, and robotics middleware like ROS are commonly required, along with familiarity with simulation environments like Gazebo or Mujoco. Strong problem-solving, collaboration, and communication skills set top performers apart as they integrate complex algorithms into real-world robotic systems. These skills and qualities are crucial for developing effective, adaptive robotic solutions that perform sophisticated manipulation tasks in dynamic environments.

What are some common challenges faced when applying reinforcement learning in robotics manipulation tasks?

A common challenge in robotics manipulation with reinforcement learning (RL) is dealing with the complexity and unpredictability of real-world environments. Unlike simulations, physical robots must handle noisy sensors, actuator delays, and unexpected interactions with objects. Training RL models can also be time-consuming and data-intensive, requiring robust simulation environments or safe real-world data collection strategies. Collaboration with hardware engineers and domain experts is often essential to troubleshoot issues and optimize learning efficiency. Successful practitioners are adaptable and proactive in bridging the gap between theory and real-world robotic performance.

What is the difference between Robotics Manipulation Reinforcement Learning vs Robotics Software Engineer?

AspectRobotics Manipulation Reinforcement LearningRobotics Software Engineer
Required CredentialsAdvanced degrees in AI, Robotics, or related fields; knowledge of reinforcement learningBachelor's or master's in Computer Science, Robotics, or Software Engineering
Work EnvironmentResearch labs, AI startups, academia focusing on machine learning applications in roboticsIndustrial settings, manufacturing, or tech companies developing robotic systems
Industry UsageDeveloping algorithms for robotic manipulation tasks using reinforcement learningBuilding, testing, and deploying robotic software systems

Robotics Manipulation Reinforcement Learning specialists focus on creating algorithms that enable robots to learn manipulation tasks through reinforcement learning techniques. In contrast, Robotics Software Engineers develop and maintain the software systems that control robotic hardware. While both roles require programming skills, the former emphasizes machine learning and AI research, whereas the latter concentrates on software development and integration in robotic applications.

What is Robotics Manipulation Reinforcement Learning?

Robotics Manipulation Reinforcement Learning is a field of artificial intelligence where robots learn to interact with and manipulate objects in their environment through trial and error, using feedback to improve their performance. This involves developing algorithms that enable robots to autonomously acquire complex motor skills, such as grasping, pushing, or assembling objects, without explicit human programming for every task. Reinforcement learning provides the framework for robots to optimize their actions by receiving rewards or penalties based on their success in manipulating objects, making them more adaptable to new and unstructured environments.
Infographic showing various Robotics Manipulation Reinforcement Learning job openings in the United States as of June 2026, with employment types broken down into 100% Full Time. Highlights an 92% Physical, 2% Hybrid, and 6% Remote job distribution, with an average salary of $96,000 per year, or $46.2 per hour.
Robotics Software Engineer - Grasping

Robotics Software Engineer - Grasping

Intrinsic

Mountain View, CA

$174K - $237K/yr

Other

Posted 26 days ago

Job description

Role

As a Robotics Software Engineer, you will develop innovative algorithms and strategies to facilitate robust grasping and manipulation in complex, real-world manufacturing environments. You will be responsible for abstracting the inherent complexity of robotic manipulation into intuitive, seamless workflows. By building a software layer that possesses a deep understanding of manufacturing tasks, you enable users to transition from design to execution without needing deep subject matter expertise. Working alongside a diverse team of roboticists and application engineers, you will integrate and validate solutions across various industrial tasks and contribute to the launch of impactful robotics products.

How your work moves the mission forward
  • Design and implement robust and efficient production-ready algorithms for robotic grasping and manipulation.
  • Identify opportunities to apply cutting-edge advancements in robotics and apply them to practical industrial problems.
  • Transform complex partner requirements into highly reliable and functional technical outcomes.
  • Improve our robotics software framework and contribute to a reliable product.
Skills you will need to be successful
  • Master's degree  in Robotics, Computer Science, or a related field, with 5+ years of experience in robotic manipulation.
  • Strong foundation in linear algebra, spatial transformations, and rigid body dynamics.
  • Hardware Experience: Direct experience testing and iterating on physical robots.
  • 3 years of professional experience programming robotics software in C++ and Python,  with a proven track record of shipping production-quality code.
Skills that will differentiate your candidacy
  • PhD in Robotics and Machine Learning,  Reinforcement Learning, or a related field with a focus on robotic manipulation.
  • ML Frameworks: Deep expertise with JAX, TensorFlow, or PyTorch.
  • Experience in developing the entire stack: ranging from writing kinematics, motion generation, to system integration and testing. 

The base salary for this full-time position is between $174,400 - $237,800 (USD) + 15% bonus + equity + benefits. Your recruiter will share more about the specific salary range + bonus + equity for your targeted location and role during the hiring process.

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