Staff Robotics Engineer / Tech Lead – Whole-Body Control & Robot Learning
Xpengmotors
·May 8, 2026
- Salary
- $215k – $364k
- Location
- Santa Clara, CA · Mountain View, California, United States
- Department
- Robotics Center
- Seniority
- Senior
- Education
- PhD
- Source
- Greenhouse
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:
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Develop control and learning-based algorithms for humanoid robot locomotion, whole-body control, motion generation, and sim-to-real transfer.
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Contribute to the technical direction of the robotics team by identifying key problems, proposing practical solutions, and helping prioritize engineering efforts.
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Work with simulation, software, hardware, AI, data, and China-based engineering teams to translate robot performance goals into executable plans.
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Mentor other engineers through design reviews, code reviews, experiments, and technical discussions.
Minimum Requirements:
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Master’s or Ph.D. degree in Robotics, Mechanical Engineering, Electrical Engineering, Computer Science, or a related field.
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5+ years of relevant experience in reinforcement learning, robotics, robot learning, control systems, or related areas.
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Strong background in robot dynamics, control, motion planning, reinforcement learning, imitation learning, or whole-body control.
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Familiarity with modern robot learning methods such as PPO, SAC, behavior cloning, diffusion policies, imitation learning, etc.
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Excellent communication skills, with the ability to work across disciplines, locations, and organizational boundaries.
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Strong ownership mindset and ability to operate effectively in a fast-moving, ambiguous, research-to-product environment.
Preferred Requirements:
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Publications or strong project experience in robotics, reinforcement learning, legged locomotion, humanoid control, or embodied AI are a plus.
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Experience technically leading projects or mentoring other engineers.
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Hands-on experience with legged robot control, testing, or operation.
What do we provide:
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A supportive, engaging environment with opportunities to make a significant impact on the future of robotics.
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Opportunities to work on cutting-edge technologies with top talent in the field.
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Competitive compensation, equity, benefits.
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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.
Skills
Machine Learning
