Control Systems Architect

Bedrock Robotics Inc • San Francisco, CA

1d • Onsite

About The Position

At Bedrock, we’re moving AI out of the lab and into the real world. Our team is composed of industry 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 machinery across the country, accelerating project schedules of billion-dollar infrastructure projects and improving safety on job sites. Backed by $350M in funding, we’re working quickly to close the gap between America's surging demand for housing, data centers, manufacturing hubs, and the construction industry's growing labor shortage.
This is where algorithms meet steel-toed boots. You’ll collaborate with construction veterans and world-class engineers to solve physical-world problems that simulations can’t touch. If you're ready to apply cutting-edge technology to solve meaningful problems alongside a talented team—we'd love to have you join us.

Bedrock is bringing autonomy to the construction industry! We’re looking for a highly motivated controls and system identification engineer to help advance our controls and simulation capabilities. The role will involve understanding and building out a key part of our onboard and offboard system. You will be responsible for understanding the system dynamics of complex 100,000lbs construction robots and distilling it down to models that can be used for onboard controls, reinforcement learning and system simulation and evaluation.

Requirements

• 5+ Years of professional engineering or research experience in control and real time embedded systems.
• Experience developing control laws for base vehicle and automated arms (Linear control, Computed torque, vehicle dynamics, impedance control, MPC)
• MSc or PhD in Control, Robotics or Computer Science
• Strong programming skills (C++, Python)
• Strong data analysis skills
• Experience working on safety critical systems
• Based in Bay Area with ability to be onsite at our testing facility and SF office on a daily/weekly basis

Nice To Haves

• Experience with Pose Estimation systems
• Experience with ML training pipelines (especially RL using learned or simulated plant models)
• Experience with CAN bus
• Experience with Rust programming language

Responsibilities

• System identification and modeling: Collaborating with the team to identify and learn the plant models of various machines.
• Onboard control: Developing learned or traditional control laws applicable across different types of earth-moving equipment.
• Offboard ML/Eval: Build the framework to use these system models and control laws for closed loop model training and offboard simulation based system evaluation.
• Safety Compliance: Working closely with the safety team to ensure that the implementation of the control laws meets all safety requirements.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level