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About the Role
We are building our first fleet of autonomous construction machines and are seeking a Controls and Robot Learning Engineer. In this role, you will contribute to the development of crucial components of our onboard and offboard autonomy system. You will be responsible for creating models to be used for onboard controls, as well as analyzing, evaluating and simulating the system dynamics of complex, 100,000-pound construction robots.
Responsibilities
- 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.
- Build models that capture the state and control input propagation of complex construction robots like excavators.
- Analyze, evaluate and simulate the system dynamics of complex, 100,000-pound construction robots.
Requirements
- 5+ years of professional engineering or research experience in control and real-time embedded systems
- 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
- MPC
- Reinforcement Learning
- linear and non linear control
- computed torque
- vehicle dynamics
- impedance control
- System Identification
- Modeling
- robot arm geometry
- system calibration
- C++
- Rust
- Python
- data analysis
- machine learning training pipelines
- pose estimation
- hydraulic systems
Location
- SF
- NY
Work Type
- flexible
Experience Level
- 5+ years
Education Level
- MSc or PhD in Computer Science or Robotics
About the Company
- At Bedrock, we're moving AI out of the lab and into the real world.
- Our team includes veterans who helped launch Waymo, scaled Segment to a $3.2B acquisition, and grew Uber Freight to $5B in revenue.
- Today, we're deploying autonomous systems on heavy construction equipment across the country, improving safety on job sites and accelerating schedules on critical infrastructure projects.
- We are not debating the future of AI. We are deploying it in the real world.
- In just two years, we've raised $350M and achieved the first fully autonomous excavator deployments in construction.
- This is where algorithms meet steel-toed boots.
- You'll work alongside construction veterans and world-class engineers to solve physical-world problems that simulations can't touch.
- If you're ready to do meaningful work on hard problems, we'd love to have you join us.