Strong background in robot dynamics , control, motion planning, reinforcement learning, imitation learning , or whole-body control. * Familiarity with modern robot learning methods such as PPO, SAC ...
Strong background in robot dynamics , control, motion planning, reinforcement learning, imitation learning , or whole-body control. * Familiarity with modern robot learning methods such as PPO, SAC ...
You will design, train, and deploy algorithms that enable robots to interact intelligently and ... imitation learning. * Experience with distributed deep learning systems.
You will design, train, and deploy algorithms that enable robots to interact intelligently and ... imitation learning. * Experience with distributed deep learning systems.
... learned robotic behaviors) • Strong applied ML fundamentals: policy learning (imitation learning, RL, or diffusion policies), neural network architecture design, training infrastructure • ...
... learned robotic behaviors) • Strong applied ML fundamentals: policy learning (imitation learning, RL, or diffusion policies), neural network architecture design, training infrastructure • ...
No preference between model-based learning, reinforcement learning, or imitation learning * Sim-to-real or real robot data * Experience building policies with multimodal inputs (vision, depth, force ...
No preference between model-based learning, reinforcement learning, or imitation learning * Sim-to-real or real robot data * Experience building policies with multimodal inputs (vision, depth, force ...
... learned robotic behaviors) • Strong applied ML fundamentals: policy learning (imitation learning, RL, or diffusion policies), neural network architecture design, training infrastructure • ...
... learned robotic behaviors) • Strong applied ML fundamentals: policy learning (imitation learning, RL, or diffusion policies), neural network architecture design, training infrastructure • ...
You will mentor junior scientists building RL and imitation learning pipelines, provide hands-on technical direction on sim-to-real transfer, foresee pitfalls in robot learning workflows before they ...
You will mentor junior scientists building RL and imitation learning pipelines, provide hands-on technical direction on sim-to-real transfer, foresee pitfalls in robot learning workflows before they ...
You will mentor junior scientists building RL and imitation learning pipelines, provide hands-on technical direction on sim-to-real transfer, foresee pitfalls in robot learning workflows before they ...
You will mentor junior scientists building RL and imitation learning pipelines, provide hands-on technical direction on sim-to-real transfer, foresee pitfalls in robot learning workflows before they ...
Founding Research Scientist, Robot Learning
San Francisco, CA · On-site
$225K - $300K/yr
Led a consequential technical direction in robot learning, reinforcement learning, imitation learning, or embodied foundation models and can show how your decisions changed the resulting system or ...
Founding Research Scientist, Robot Learning
San Francisco, CA · On-site
$225K - $300K/yr
Led a consequential technical direction in robot learning, reinforcement learning, imitation learning, or embodied foundation models and can show how your decisions changed the resulting system or ...
Senior Research Scientist - Manipulation
$107K - $136K/yr
Research large-scale VLAs and other multimodal behavior models that connect perception, language, reasoning, and continuous robot action. * Develop imitation-learning and reinforcement-learning ...
Senior Research Scientist - Manipulation
$107K - $136K/yr
Research large-scale VLAs and other multimodal behavior models that connect perception, language, reasoning, and continuous robot action. * Develop imitation-learning and reinforcement-learning ...
Senior Research Scientist - Manipulation
Boston, MA · On-site
$150K - $300K/yr
Research large-scale VLAs and other multimodal behavior models that connect perception, language, reasoning, and continuous robot action. * Develop imitation-learning and reinforcement-learning ...
Quick apply
Senior Research Scientist - Manipulation
Boston, MA · On-site
$150K - $300K/yr
Research large-scale VLAs and other multimodal behavior models that connect perception, language, reasoning, and continuous robot action. * Develop imitation-learning and reinforcement-learning ...
You will design large-scale behavior cloning and imitation learning pipelines, build hierarchical skill systems, and integrate learned components into a complex, real-world robotic system. You'll ...
You will design large-scale behavior cloning and imitation learning pipelines, build hierarchical skill systems, and integrate learned components into a complex, real-world robotic system. You'll ...
$72K - $92K/yr
Research large-scale VLAs and other multimodal behavior models that connect perception, language, reasoning, and continuous robot action. * Develop imitation-learning and reinforcement-learning ...
$72K - $92K/yr
Research large-scale VLAs and other multimodal behavior models that connect perception, language, reasoning, and continuous robot action. * Develop imitation-learning and reinforcement-learning ...
Responsibilities : • Design, train, and deploy ML models for robotic control, quality prediction, and process optimization • Develop reinforcement learning and imitation learning systems for ...
Responsibilities : • Design, train, and deploy ML models for robotic control, quality prediction, and process optimization • Develop reinforcement learning and imitation learning systems for ...
You will design large-scale behavior cloning and imitation learning pipelines, build hierarchical skill systems, and integrate learned components into a complex, real-world robotic system. You'll ...
You will design large-scale behavior cloning and imitation learning pipelines, build hierarchical skill systems, and integrate learned components into a complex, real-world robotic system. You'll ...
Senior Research Scientist - Manipulation
Boston, MA · On-site
$150K - $300K/yr
Research large-scale VLAs and other multimodal behavior models that connect perception, language, reasoning, and continuous robot action. * Develop imitation-learning and reinforcement-learning ...
Senior Research Scientist - Manipulation
Boston, MA · On-site
$150K - $300K/yr
Research large-scale VLAs and other multimodal behavior models that connect perception, language, reasoning, and continuous robot action. * Develop imitation-learning and reinforcement-learning ...
Senior Research Scientist - Manipulation
Boston, MA · On-site
$107K - $136K/yr
Research large-scale VLAs and other multimodal behavior models that connect perception, language, reasoning, and continuous robot action. * Develop imitation-learning and reinforcement-learning ...
Senior Research Scientist - Manipulation
Boston, MA · On-site
$107K - $136K/yr
Research large-scale VLAs and other multimodal behavior models that connect perception, language, reasoning, and continuous robot action. * Develop imitation-learning and reinforcement-learning ...
Develop and train end-to-end robot learning models, including vision-language-action (VLA) family of models, imitation learning policies, and reinforcement learning agents for manipulation ...
Develop and train end-to-end robot learning models, including vision-language-action (VLA) family of models, imitation learning policies, and reinforcement learning agents for manipulation ...
Design and implement GPU-accelerated reinforcement learning and imitation learning environments in ... Create robot embodiment validation tests (joint kinematics, actuator response, contact behavior) to ...
Design and implement GPU-accelerated reinforcement learning and imitation learning environments in ... Create robot embodiment validation tests (joint kinematics, actuator response, contact behavior) to ...
Design and implement GPU-accelerated reinforcement learning and imitation learning environments in ... Create robot embodiment validation tests (joint kinematics, actuator response, contact behavior) to ...
Design and implement GPU-accelerated reinforcement learning and imitation learning environments in ... Create robot embodiment validation tests (joint kinematics, actuator response, contact behavior) to ...
Senior AI Research Scientist, Robotics & Embodied AI
Mountain View, CA · On-site
$115K - $147K/yr
Develop novel algorithms and learning approaches for intelligent robotic systems * Research and develop methods for robot learning, imitation learning, reinforcement learning, and learning-based ...
Senior AI Research Scientist, Robotics & Embodied AI
Mountain View, CA · On-site
$115K - $147K/yr
Develop novel algorithms and learning approaches for intelligent robotic systems * Research and develop methods for robot learning, imitation learning, reinforcement learning, and learning-based ...
Robotic Imitation Learning information
See salary details
$15.38 - $18.12
18% of jobs
$20.65 is the 25th percentile. Wages below this are outliers.
$18.12 - $20.85
7% of jobs
$20.85 - $23.58
10% of jobs
$23.58 - $26.31
10% of jobs
The median wage is $27.36 / hr.
$26.31 - $29.04
14% of jobs
$29.04 - $31.77
15% of jobs
$32.15 is the 75th percentile. Wages above this are outliers.
$31.77 - $34.51
12% of jobs
$34.51 - $37.24
5% of jobs
$37.24 - $39.97
3% of jobs
$39.97 - $42.70
2% of jobs
$42.70 - $45.43
4% of jobs
$15
$28
$45
How much do robotic imitation learning jobs pay per hour?
As of Sep 13, 2026, the average hourly pay for robotic imitation learning in the United States is $28.24, according to ZipRecruiter salary data. Most workers in this role earn between $22.12 and $32.93 per hour, depending on experience, location, and employer.
What is robotic imitation learning?
Robotic imitation learning is a technique in robotics where robots learn to perform tasks by observing and mimicking human actions or demonstrations. Instead of being explicitly programmed, the robot uses data from demonstrations to infer the necessary actions or behaviors. This approach can help robots learn complex tasks more efficiently and adapt to new situations by leveraging human expertise. It is widely used in areas such as manufacturing, service robotics, and autonomous vehicles.
What are some typical challenges faced when working on robotic imitation learning projects, and how can they be addressed?
Professionals in robotic imitation learning often encounter challenges such as collecting high-quality demonstration data, ensuring generalization across varied tasks, and managing the sim-to-real gap when transferring learned behaviors from simulation to physical robots. Addressing these challenges typically involves developing robust data collection pipelines, leveraging domain adaptation techniques, and collaborating closely with hardware engineers to fine-tune models in real-world environments. Teamwork with researchers specializing in computer vision, reinforcement learning, and robotics hardware is crucial for overcoming these hurdles and achieving reliable robot performance.
What are the key skills and qualifications needed to thrive in robotic imitation learning, and why are they important?
To thrive in Robotic Imitation Learning, you need a strong background in robotics, machine learning, and computer science, often supported by an advanced degree in a related field. Familiarity with programming languages like Python or C++, machine learning frameworks (e.g., TensorFlow, PyTorch), and robotics simulation tools such as ROS or Gazebo is essential. Strong problem-solving skills, creativity, and effective communication are crucial soft skills for developing innovative solutions and collaborating with multidisciplinary teams. These skills and qualities are important to advance the field, ensure robust algorithm development, and enable efficient deployment of robotic systems in real-world environments.
What is the difference between Robotic Imitation Learning vs Robotic Software Engineer?
| Aspect | Robotic Imitation Learning | Robotic Software Engineer |
|---|---|---|
| Required Credentials | Advanced degrees in AI, Robotics, or Computer Science | Bachelor's or Master's in Software Engineering, Computer Science, or related fields |
| Work Environment | Research labs, AI development teams, robotics startups | Industrial, research, or manufacturing settings involving robotics software development |
| Industry Usage | Developing algorithms for robots to learn behaviors through imitation | Designing, coding, and maintaining robotic control software |
Robotic Imitation Learning focuses on creating algorithms that enable robots to learn behaviors by mimicking demonstrations, often requiring expertise in AI and machine learning. In contrast, a Robotic Software Engineer develops and maintains the software systems that control robots, emphasizing programming skills and software development. Both roles are essential in robotics but serve different functions within the industry.
What other helpful pages are available for Robotic Imitation Learning?
Other pages related to Robotic Imitation Learning:
Staff Robotics Engineer / Tech Lead - Whole-Body Control & Robot Learning
Santa Clara, CA • On-site
Full-time
Re-posted 6 days ago
Job description
XPENG is a leading smart technology company at the forefront of innovation, integrating advanced AI and autonomous driving technologies into its vehicles, including electric vehicles (EVs), electric vertical take-off and landing (eVTOL) aircraft, and robotics. With a strong focus on intelligent mobility, XPENG is dedicated to reshaping the future of transportation through cutting-edge R&D in AI, machine learning, and smart connectivity.
We are now expanding into the development of general-purpose humanoid robots aimed at automating repetitive tasks and assisting people in their daily lives.
We are seeking a highly motivated Staff Robotics Engineer / Tech Lead to join our US robotics team. This role is ideal for a strong hands-on engineer who can contribute deeply to humanoid robot control, whole-body motion generation, robot learning, and sim-to-real deployment, while helping coordinate technical direction and mentor a small team. The ideal candidate brings strong engineering judgment, clear communication, and the ability to help other engineers move faster and make better technical decisions.
Key Responsibilities:
What do we provide:
The base salary range for this full-time position is $215,280-$364,320, in addition to bonus, equity and benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training.
We are an Equal Opportunity Employer. It is our policy to provide equal employment opportunities to all qualified persons without regard to race, age, color, sex, sexual orientation, religion, national origin, disability, veteran status or marital status or any other prescribed category set forth in federal or state regulations.
We are now expanding into the development of general-purpose humanoid robots aimed at automating repetitive tasks and assisting people in their daily lives.
We are seeking a highly motivated Staff Robotics Engineer / Tech Lead to join our US robotics team. This role is ideal for a strong hands-on engineer who can contribute deeply to humanoid robot control, whole-body motion generation, robot learning, and sim-to-real deployment, while helping coordinate technical direction and mentor a small team. The ideal candidate brings strong engineering judgment, clear communication, and the ability to help other engineers move faster and make better technical decisions.
Key Responsibilities:
- Develop control and learning-based algorithms forhumanoid robot locomotion, whole-body control, motion generation, and sim-to-real transfer.
- Contribute to the technical direction of the robotics team by identifying key problems, proposing practical solutions, and helping prioritize engineering efforts.
- Work with simulation, software, hardware, AI, data, and China-based engineering teams to translate robot performance goals into executable plans.
- Mentor other engineers through design reviews, code reviews, experiments, and technical discussions.
- Master's or Ph.D. degree in Robotics, Mechanical Engineering, Electrical Engineering, Computer Science, or a related field.
- 5+ years of relevant experience inreinforcement learning, robotics, robot learning, control systems, or related areas.
- Strong background in robot dynamics, control, motion planning, reinforcement learning, imitation learning, or whole-body control.
- Familiarity with modern robot learning methods such as PPO, SAC, behavior cloning, diffusion policies, imitation learning, etc.
- Excellent communication skills, with the ability to work across disciplines, locations, and organizational boundaries.
- Strong ownership mindset and ability to operate effectively in a fast-moving, ambiguous, research-to-product environment.
- Publications or strong project experience in robotics, reinforcement learning, legged locomotion, humanoid control, or embodied AI are a plus.
- Experience technically leading projects or mentoring other engineers.
- Hands-on experience with legged robot control, testing, or operation.
What do we provide:
- A supportive, engaging environment with opportunities to make a significant impact on the future of robotics.
- Opportunities to work on cutting-edge technologies with top talent in the field.
- Competitive compensation, equity, benefits.
- Lunches, snacks, and team activities.
The base salary range for this full-time position is $215,280-$364,320, in addition to bonus, equity and benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training.
We are an Equal Opportunity Employer. It is our policy to provide equal employment opportunities to all qualified persons without regard to race, age, color, sex, sexual orientation, religion, national origin, disability, veteran status or marital status or any other prescribed category set forth in federal or state regulations.