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Robotics Manipulation Reinforcement Learning Jobs

... and manipulation challenges and deliver breakthrough results on physical hardware. The primary ... Collaborate closely with the robotics and hardware teams to diagnose system-level issues and co ...

Robotics Manipulation Engineer Responsibilities: * Partner with server hardware and operations ... deep learning, reinforcement learning and imitation learning techniques used in robotics

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Robotics Manipulation Reinforcement Learning information

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$84K

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$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.
Member of Technical Staff - Robot Manipulation & Learning, Frontier AI Robotics

Member of Technical Staff - Robot Manipulation & Learning, Frontier AI Robotics

Amazon

San Francisco, CA • On-site

Full-time

Posted 12 days ago


Amazon rating

7.4

Company rating: 7.4 out of 10

Based on 6,874 frontline employees who took The Breakroom Quiz

6th of 39 rated national retailers


Job description

We are seeking to hire software engineers who are excited about research for robot manipulation with the goal of developing manipulation systems at human-level performance. Our strategy focuses on a real2sim2real pipeline that learns from large scale human videos and leverage simulation and reinforcement learning to bridge the human-to-robot embodiment gap.
Key job responsibilities
Learning manipulation: Design and implement robot learning algorithms for manipulation
Leverage vision models to extract 3D hand-object manipulation information from real-world situations
Develop large-scale real2sim2real pipeline for manipulation
Multimodal Sensor Fusion: Integrate tactile sensing, proprioception and vision into the learning pipeline
About the team
At Frontier AI & Robotics (FAR), we're not just advancing robotics - we're reimagining it from the ground up. Our team is building the future of intelligent robotics through frontier foundation models and end-to-end learned systems

We tackle some of the most challenging problems in AI and robotics, from developing sophisticated perception systems to creating adaptive manipulation strategies that work in complex, real-world scenarios.
What sets us apart is our unique combination of ambitious research vision and practical impact. We leverage Amazon's massive computational infrastructure and rich real-world datasets to train and deploy state-of-the-art foundation models. Our work spans the full spectrum of robotics intelligence - from multimodal perception using images, videos, and sensor data, to sophisticated manipulation strategies that can handle diverse real-world scenarios

We're building systems that don't just work in the lab, but scale to meet the demands of Amazon's global operations.
Join us if you're excited about pushing the boundaries of what's possible in robotics, working with world-class researchers, and seeing your innovations deployed at unprecedented scale.


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Amazon.com, Inc., commonly known as Amazon, is an American multinational technology company. It was founded by Jeff Bezos in 1994 and initially started as an online marketplace for books. Since then, Amazon has expanded its operations and become one of the largest e-commerce companies in the world. Amazon's primary business is its online retail platform, where customers can purchase a vast array of products, including electronics, clothing, books, home goods, and much more. The company offers a convenient and user-friendly shopping experience, with features such as fast shipping, customer reviews, and personalized recommendations. In addition to its e-commerce platform, Amazon has diversified its business into various other areas. One of its notable ventures is Amazon Web Services (AWS), a comprehensive cloud computing platform that provides services such as storage, compute power, and database management to individuals and businesses. AWS has become a leader in the cloud computing industry, powering many websites and applications worldwide. Amazon has also developed its own consumer electronics, including the popular Amazon Kindle e-reader, Fire tablets, Fire TV streaming devices, and the Alexa-powered Echo smart speakers. The Alexa voice assistant, integrated into these devices, allows users to interact with their devices using voice commands, perform tasks, and access information. Furthermore, Amazon has expanded into media and entertainment. It operates Prime Video, a streaming service that offers a wide range of movies, TV shows, and original content. Amazon Music provides a platform for streaming and purchasing digital music, while Audible offers audiobooks and other audio content. The company's commitment to customer satisfaction and convenience is demonstrated by its membership program, Amazon Prime. Prime members receive various benefits, including free two-day shipping, access to streaming services, exclusive deals, and more.

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It services, book publishers, retail, real estate and computer and electronic product manufacturing

Company size

10,000+ Employees

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Seattle, WA, US