Software Engineer, State Estimation & Localization
Bedrock Robotics · San Francisco, CA
About this role
## Software Engineer, State Estimation & Localization **About Bedrock** At Bedrock, we’re moving AI out of the lab and into the real world—deploying autonomous systems on heavy construction equipment across the country to improve safety and accelerate critical infrastructure schedules. 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. --- ## Role We’re looking for a **Software Engineer** to develop **state-estimation systems** that allow autonomous machines to understand their **position, orientation, motion, and configuration**. You’ll build production software that fuses data from **GNSS, IMUs, lidar, machine sensors, and other sources** in rugged environments—helping machines operate precisely, detect unreliable inputs, and respond safely when data is 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 via **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 to 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 full autonomy stack --- ## What we’re looking for - **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**, **sensor calibration** - Strong production software skills in **Rust or modern C++** (our stack is primarily **Rust**; we support experienced C++ engineers ramping up) - Experience measuring estimator performance using **ground truth, recorded data, simulation, and real-world testing** - Strong debugging and data-analysis skills across algorithms, software, sensors, and hardware - Degree in **Robotics, Computer Science, EE, ME, Applied Mathematics**, or related field (or equivalent practical experience) --- ## Ways to stand out - 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 optimizatio
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