Software Engineer, State Estimation & Localization

At Bedrock were 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 were deploying autonomous systems on heavy construction equipment across the country improving safety on job sites and accelerating schedules on critical infrastructure projects.

Were not here debating the future of AI. Were deploying it in the real just two years weve raised $350M and achieved the first fully autonomous excavator deployments in construction.

This is where algorithms meet steel-toed boots. Youll work alongside construction veterans and world-class engineers to solve physical-world problems that simulations cant touch. If youre ready to do meaningful work on hard problems wed love to have you join us.

Were looking for a Software Engineer to develop the state-estimation systems that allow autonomous machines to understand their position orientation motion and configuration. Youll 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.

• 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

• Collaborate with controls perception safety hardware and systems teams to improve the performance of the complete autonomy system

• 4 years of professional engineering or applied research experience in state estimation localization navigation SLAM or sensor fusion

• Strong foundations in probabilistic estimation linear algebra 3D geometry and numerical methods

• Hands-on experience with one or more of GNSS/INS fusion Kalman filtering factor graphs lidar or visual odometry point-cloud registration or sensor calibration

• Strong production software skills in Rust or modern C. Our production stack is primarily Rust and we will support experienced C engineers as they ramp up

• Experience measuring estimator performance using ground truth recorded data simulation and real-world testing

• Strong debugging and data-analysis skills including the ability to investigate problems across algorithms software sensors and hardware

• A degree in Robotics Computer Science Electrical Engineering Mechanical Engineering Applied Mathematics or a related field or equivalent practical experience

• Experience deploying state-estimation systems on autonomous vehicles robots or embedded platforms

• Experience with estimator monitoring uncertainty fault detection redundancy or safety-relevant systems

• Experience with nonlinear optimization factor graphs or smoothing

• Deep knowledge of GNSS inertial sensing lidar sensor timing calibration and real-world failure modes

• Experience with lidar localization ICP continuous-time estimation or articulated-machine estimation

• Experience building offline reference estimators or independent ground-truth systems

• Production experience with Rust

• Familiarity with construction mining agricultural or other heavy industrial machines

• Based in San Francisco with the ability to be onsite at our SF office 3 day a week

Bedrock Robotics is an Equal Opportunity Employer

Were 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.

Required Experience:

IC