Controls and Robot Learning Engineer
Hybrid (San Francisco, CA)Full-timePosted 2mo ago
About the role
Join Bedrock Robotics to develop onboard and offboard autonomy for autonomous construction machines. You’ll build models and control laws for 100,000-pound robots, perform system identification and modeling, and contribute to deploying advanced autonomy in real-world construction environments.
Responsibilities
- Onboard Control: Develop control laws for the base vehicle and automated arms, utilizing techniques such as MPC, Reinforcement Learning, linear and non linear control, computed torque, vehicle dynamics, and impedance control.
- System Identification and Modeling: Build models that capture the state and control input propagation of complex construction robots like excavators. This involves understanding the direct and inverse geometry of robot arms (4 to 7 DOFs), vehicle dynamics, and overall system calibration.
Qualifications
- 5+ years of professional engineering or research experience in control and real-time embedded systems
- MSc or PhD in Computer Science or Robotics
- Deep understanding of reinforcement learning, imitation learning, and optimization for dynamic systems
- Strong programming skills (C++/Rust, Python)
- Strong data analysis skills
- Experience with safety-critical systems
Skills
Required:Control theory and onboard controlSystem identification and modelingProgrammingSafety-critical systemsData analysis
Last updated Sep 10, 2026. Interested? Apply on the company site.
About Bedrock Robotics
Advanced Autonomy for the Built World
Advanced Autonomy for the Built World
AutonomyBedrock Operatorautonomyheavy machineryindustrial automationindustrial roboticsmachine intelligenceon-site autonomy
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