Controls and Robot Learning Engineer (Robotics)

Location: San Francisco, CA; hybrid. Flexible arrangements may be considered for candidates in other locations, especially where an office is available.

Company

hirify.global develops autonomous systems for heavy construction equipment and deploys them on real-world construction sites.

What you will do

• Develop control laws for base vehicles and automated construction-machine arms.
• Apply MPC, reinforcement learning, linear and nonlinear control, computed torque, vehicle dynamics, and impedance control.
• Build models describing state and control-input propagation for complex robots such as excavators.
• Analyze, evaluate, and simulate the dynamics of 100,000-pound construction robots.
• Model robot-arm geometry, vehicle dynamics, system calibration, and hydraulic systems.

Requirements

• 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 in C++, Rust, and Python, plus strong data analysis skills.
• Experience with safety-critical systems and production autonomy environments.
• Experience with machine learning training pipelines, pose estimation systems, and reinforcement learning using learned or simulated plant models.

Nice to have

• Practical application of reinforcement learning or model predictive control for production autonomy.
• Experience controlling and modeling hydraulic systems.
• Experience working with pose estimation systems.

Culture & Benefits

• Work alongside construction specialists and engineers on physical-world autonomy problems.
• Contribute to the first fleet of autonomous construction machines.
• Flexible role arrangements may be considered for candidates outside the listed location.
• Inclusive workplace with equal-opportunity employment and reasonable accommodations during hiring.