5 часов назад
Lead AI Research Engineer, Embodied Systems (Robotics)
190 000 - 265 000$
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Lead AI Research Engineer, Embodied Systems (Robotics): Engineering onboard AI, data collection, teleoperation, and on-robot reinforcement learning systems that turn embodied AI into real-world robot behavior with an accent on real-time deployment, closed-loop evaluation, and physical robot integration. Focus on setting system architecture, integrating sensing, control, and compute through ROS/ROS2, and improving policies from real-world performance in demanding industrial environments.
Location: Milpitas, California, United States; 5 days per week in-office
Salary: $190,000–$265,000 USD annually, plus bonus and equity
Company
is an AI robotics company developing Physical AI-powered robots for dull, dirty, and dangerous industrial work, with a focus on real-world deployment and scalability.
What you will do
- Lead the engineering of the embodied systems powering the data flywheel, including onboard inference, data collection, teleoperation, and on-robot reinforcement learning.
- Set the technical direction and architecture for running, evaluating, and improving learned models on physical robots.
- Deliver end-to-end systems from robot bring-up through reliable, real-time operation in demanding industrial environments.
- Own on-robot deployment and closed-loop policy evaluation, converting real-world performance into measurable improvements.
- Partner with robotics software and ML research teams to align interfaces and priorities across the stack.
- Mentor engineers and raise the technical bar for embodied systems.
Requirements
- Bachelor’s or Master’s degree in Computer Science, Robotics, Electrical Engineering, or a related field with significant relevant experience, or a PhD.
- Track record of leading complex robotic or embodied systems end-to-end and setting technical direction.
- Strong proficiency in C++ and Python, with solid systems programming and real-time, performance-critical engineering skills.
- Hands-on experience with ROS/ROS2 and robot middleware, including real-time integration of sensing, control, and compute.
- Experience integrating and deploying ML models or policies into real-time robotic or autonomous systems, with an emphasis on system ownership and engineering.
- Must collaborate in the office 5 days per week.
Nice to have
- Experience with teleoperation and large-scale robot data collection systems, including VR, UR, GELLO, or UMI.
- Experience with on-robot reinforcement learning or closed-loop policy improvement.
- Familiarity with VLA, imitation learning, behavior cloning, manipulation stacks, whole-body control interfaces, or real-time middleware tuning.
Culture & Benefits
- Competitive stock options and equity programs.
- Health, dental, and vision insurance.
- 401(k) plan.
- Visa sponsorship and green card support are available for qualified candidates.
- Lunches and dinners, a stocked kitchen, and regular team-building events.
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