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 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.

Summary: We are seeking a Pose & Localization Software Engineer to develop robust state estimation systems for autonomous heavy construction equipment. This role involves working with real machines in dynamic environments, ensuring precise vehicle state estimation even as the terrain evolves.

Responsibilities:

• Design and implement pose estimation and localization pipelines for onboard autonomy

• Fuse data from GNSS/INS, IMU, visual odometry, and LiDAR scan matching

• Adapt offline, large-scale SLAM systems to real-time onboard constraints

• Handle dynamic scenes, including changing terrain and environments

• Balance accuracy, latency, and compute constraints on embedded systems

• Partner with perception, controls, and safety teams to debug system-level issues

• Evaluate performance using field data and offline analysis

Required skills:

• 5+ years in pose estimation, localization, SLAM, or state estimation

• Strong C++ (production-quality systems code)

• Experience with real sensor data (IMU, GNSS, cameras, LiDAR)

• Strong foundation in linear algebra, probability, and optimization

Preferred skills:

• Graph-based SLAM or factor-graph optimization experience

• Background in GNSS/INS fusion, visual odometry, LiDAR ICP, or sensor calibration

• Experience with Rust (or interest in learning)

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.