Controls and Robot Learning Engineer

Bedrock Robotics

San Francisco, CA

Who this role is best for

A natural match if you have experience with real-time embedded systems and safety-critical control algorithms.

Best fit for

Candidates with advanced robotics or CS degrees and hands-on control system development experience
— “MSc or PhD in Computer Science or Robotics”
Individuals who have applied reinforcement learning or MPC in production environments
— “Practical application of RL or model predictive control (MPC) for control algorithms in production autonomy environments”
Professionals familiar with hydraulic system modeling and pose estimation systems
— “Experience with controlling and modeling hydraulic systems”

Things to consider

The role requires working with heavy construction equipment in real-world settings
— “You'll work alongside construction veterans and world-class engineers to solve physical-world problems that simulations can't touch”
Candidates must be prepared to handle complex, safety-critical systems
— “Experience with safety-critical systems”

How to stand out

Highlight projects involving real-time embedded systems and dynamic control algorithms
— “Develop control laws for the base vehicle and automated arms, utilizing techniques such as MPC, Reinforcement Learning, linear and non linear control”
Showcase your ability to model complex robots with high degrees of freedom
— “Build models that capture the state and control input propagation of complex construction robots like excavators”
Emphasize your experience with machine learning training pipelines and simulated plant models
— “Experience with machine learning training pipelines, especially reinforcement learning (RL) using learned or simulated plant models”

Pace · Fast PacedCollaboration · MediumAutonomy · MediumDecision Impact · TeamLevel · Senior

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

Developed 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.

Typical background

MSc or PhD in Computer Science or Robotics

Skills & requirements

Required

Control Laws DevelopmentModel Predictive Control (mpc)Reinforcement LearningLinear And Nonlinear ControlVehicle DynamicsImpedance ControlSystem Identification And ModelingRoboticsHydraulic Systems

Preferred

Machine Learning Training PipelinesReinforcement Learning (RL) Using Learned Or Simulated Plant ModelsPose Estimation Systems

Stack & domain

MPCReinforcement LearningLinear And Non Linear ControlComputed TorqueVehicle DynamicsImpedance ControlMachine Learning Training PipelinesModel Predictive ControlControlling And Modeling Hydraulic SystemsRoboticsConstruction Equipment

About the role

Original posting from Bedrock Robotics via Ashby

JOIN THE TEAM BRINGING ADVANCED AUTONOMY TO THE BUILT WORLD
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're not here debating the future of AI. We're 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.
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.
WHAT YOU'LL DO
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 a deep understanding of the direct and inverse geometry of robot arms (4 to 7 DOFs), vehicle dynamics, and overall system calibration.
WHAT WE'RE LOOKING FOR
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
WAYS TO STAND OUT FROM THE CROWD
Experience with machine learning training pipelines, especially reinforcement learning (RL) using learned or simulated plant models
Practical application of RL or model predictive control (MPC) for control algorithms in production autonomy environments
Experience working with pose estimation systems
Experience with controlling and modeling hydraulic systems
Our roles are often flexible. If you don't fit all the criteria, or are in another location (especially one where we have an office like SF or NY), please apply anyway! We'd love to consider you.
Bedrock Robotics is an Equal Opportunity Employer
We’re committed to building a diverse and inclusive workplace. We consider all qualified applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, ancestry, age, disability, veteran status, genetic information, or any other protected characteristic.
Reasonable Accommodations
We want our hiring process to be accessible to everyone. If you need an accommodation to participate in the application or interview process, please let your recruiter know so we can support you.

Source: Bedrock Robotics careers (Ashby)