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# Software Engineer, State Estimation & Localization

- **Company:** Bedrock Robotics
- **Location:** San Francisco, CA, United States
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Data Analysis, C++ (Programming Language), Software Debugging, Fault Tolerance, Regression Testing, State Estimation, Sensor Fusion, Software Engineering, Juniper, Information Technology, C++14, GNSS
- **Published:** October 31, 2026
- **Apply:** https://www.careerbuilder.com/job-details/software-engineer-state-estimation-localization-san-francisco-ca--aabc9850-d621-49c8-82cf-69cac47ed728

## About the Role

Software Engineering, Localization, Algorithms, Funding, Retrofit, Cargo/Freight, Construction, Heavy Equipment/Vehicles, Juniper Networks M-Series, Artificial Intelligence (AI), * 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

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 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

Other special aspects of the role:

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

## Description

* 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