Software Engineer

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’re looking for a Software Engineer to develop the state-estimation systems that allow autonomous machines to understand their position, orientation, motion, and configuration. You’ll build production software that combines data from GNSS, IMUs, lidar, machine sensors, and other sources in rugged environments the machines themselves are actively reshaping.

Accurate state estimation is essential to both safety and performance. Your work will help our machines operate precisely, recognize when sensor data or estimates are unreliable, and respond safely when inputs are delayed, degraded, or unavailable.

Depending on your background, you may focus on real-time sensor fusion, estimator reliability, lidar-based estimation, offline optimization, or calibration. This is a hands-on role spanning algorithm design, production software, data analysis, and testing on real machines.

What you’ll do:

• Design, implement, and deploy state-estimation and localization algorithms for autonomous construction machines

• Combine GNSS, IMU, lidar, and machine-sensor data into accurate, real-time estimates of machine position, motion, and configuration

• Improve reliability through sensor monitoring, consistency checks, fault detection, trustworthy confidence estimates, redundancy, and graceful degradation

• Handle measurements that arrive late, out of order, intermittently, or not at all

• Build ground-truth systems, offline reference estimators, metrics, and regression tests that measure performance and expose failures

• Work on related problems such as sensor calibration, clock synchronization, lidar-based arm estimation, and joint offline estimation

• Diagnose issues using field data, recorded-data replay, and simulation, then test improvements on physical machines