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About the Role
Join Bedrock in moving AI out of the lab and into the real world by deploying autonomous systems on heavy construction equipment. This role focuses on developing state-estimation systems that enable autonomous machines to understand their position, orientation, motion, and configuration, combining data from various sensors in challenging environments.
Responsibilities
- 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
Requirements
- 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++
- 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
Skills
- State estimation
- Localization
- Navigation
- SLAM
- Sensor fusion
- Probabilistic estimation
- Linear algebra
- 3D geometry
- Numerical methods
- GNSS/INS fusion
- Kalman filtering
- Factor graphs
- Lidar odometry
- Visual odometry
- Point-cloud registration
- Sensor calibration
- Rust
- C++
- Debugging
- Data analysis
Location
- San Francisco Bay Area
Work Type
- Onsite
Experience Level
- 4+ years of professional engineering or applied research experience
Education Level
- Degree in Robotics, Computer Science, Electrical Engineering, Mechanical Engineering, Applied Mathematics, or a related field, or equivalent practical experience
About the Company
- 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.
Equal Opportunity
- 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.
- 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.