Research Engineer, Robot Learning
TECHNICAL STACK · 2 TAGS
OVERVIEW
Job Description: Develop sim2real reinforcement learning (RL) training pipelines for humanoid robots. Train and test robot policies via reinforcement learning for in-home humanoid robots. Optimize training pipelines for improved performance and training speed. Modeling of physical systems (including robot dynamics, sensor modeling, contact parameter tuning) to close the gap between simulation and physical systems. Collecting, cleaning and retargeting human motion data for use in RL training pipelines. Supporting the test and debug of RL policies in simulation and on physical hardware.
Requirements: Master’s degree or foreign degree equivalent in Robotics, AI/Machine Learning, Mechanical or Electrical Engineering, Computer Science, or related field and one (1) year of experience in a Robotics & Machine Learning occupation or related in the job offered.
SKILLS:
Experience and/or education must include:
Rigid body dynamics and/or dynamical systems for training, deploying and testing reinforcement learned policies for humanoid robots.
Implement production-grade Python code for reinforcement learning (RL) and other machine learning training pipelines.
Reinforcement learned algorithms, techniques, and sim2real approaches as they pertain to robotics to perform various human-like capabilities, including whole-body loco-manipulation.
Implement and debug real-time software in C++ deployed on robots to satisfy various real-time constraints.
Model physical systems, including multi-body hybrid dynamic systems with contact, in a simulated environment to identify gaps between simulation and hardware and the ability to understand how to accurately model the hardware in simulation.
Root-cause analysis as it pertains to robotic systems and the ability to quickly troubleshoot issues.
Forward and inverse kinematics as they pertain to humanoid system training using human motion data.
REQUIREMENTS
Experience and/or education must include
- Rigid body dynamics and/or dynamical systems for training, deploying and testing reinforcement learned policies for humanoid robots.
- Implement production-grade Python code for reinforcement learning (RL) and other machine learning training pipelines.
- Reinforcement learned algorithms, techniques, and sim2real approaches as they pertain to robotics to perform various human-like capabilities, including whole-body loco-manipulation.
- Implement and debug real-time software in C++ deployed on robots to satisfy various real-time constraints.
- Model physical systems, including multi-body hybrid dynamic systems with contact, in a simulated environment to identify gaps between simulation and hardware and the ability to understand how to accurately model the hardware in simulation.
- Root-cause analysis as it pertains to robotic systems and the ability to quickly troubleshoot issues.
- Forward and inverse kinematics as they pertain to humanoid system training using human motion data.
QUESTIONS AND ANSWERS
- How much does the Research Engineer, Robot Learning at 1X Technologies pay?
- The posting lists a range of $130K–$300K per year. Ranges reflect what 1X Technologies publicly declared on the source posting.
- Where is this Research Engineer, Robot Learning role based?
- The role is based in San Carlos, CA.
- What experience does 1X Technologies expect for this role?
- The posting is tagged as a mid-level role, typically 3+ years of experience. Check the requirements section for specifics.
- Where is 1X Technologies headquartered?
- 1X Technologies is headquartered in Moss, Norway.
- How was this posting sourced?
- This role was pulled directly from 1X Technologies's Ashby careers site. Apply links open in the employer's own ATS — no reposts or aggregator middleware.
Apply links open in the employer's official ATS. Always verify recruitment messages on the company's careers page before sharing personal information.