Software Engineer, State Estimation, Localization

Jobtailor; San Francisco (CA); On-site; USD 140,000 - 190,000; Full time

Job summary

Jobtailor in San Francisco is seeking a seasoned State Estimation Engineer to build and refine localization and state-estimation systems for autonomous machines. You will fuse GNSS, IMU, lidar, and sensors to produce accurate real-time estimates, and you will ensure reliability with monitoring, fault detection, and graceful degradation.

You will collaborate with controls, perception, safety, hardware, and systems teams to advance the complete autonomy stack, with at least 4 years of related

Qualifications

• 4+ years of professional engineering or applied research 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 GNSS/INS fusion, Kalman filtering, factor graphs, lidar/visual odometry, or sensor calibration.

Responsibilities

• Develop state-estimation systems enabling autonomous machines to understand position, orientation, motion, and configuration.
• 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.
• Improve reliability through sensor monitoring, consistency checks, fault detection, confidence estimates, redundancy, and graceful degradation.
• Handle delayed, out-of-order, intermittent, or missing measurements.
• Build ground-truth systems, offline reference estimators, metrics, and regression tests.
• Collaborate with controls, perception, safety, hardware, and systems teams to improve the complete autonomy system.

Skills

State Estimation

Localization Algorithms

GNSS/INS Fusion

Rust Programming

Kalman Filtering

Sensor Fusion

3D Geometry

Linear Algebra

Data Analysis

Debugging

Education

Degree in Robotics or related field

Tools

Lidar

IMU

GNSS

Simulation

Embedded Platforms

Job description

• Develop state-estimation systems enabling autonomous machines to understand position, orientation, motion, and configuration
• 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
• Improve reliability through sensor monitoring, consistency checks, fault detection, confidence estimates, redundancy, and graceful degradation
• Handle delayed, out-of-order, intermittent, or missing measurements
• Build ground-truth systems, offline reference estimators, metrics, and regression tests
• Work on sensor calibration, clock synchronization, lidar-based arm estimation, and joint offline estimation
• Diagnose issues using field data, recorded-data replay, and simulation
• Test improvements on physical machines
• Collaborate with controls, perception, safety, hardware, and systems teams to improve 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 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
• Ability to work onsite in San Francisco 3 days per week
• Legally authorized to work in the United States
• Experience with autonomous vehicles, robots, or embedded platforms is advantageous
• Experience with estimator monitoring, uncertainty, fault detection, redundancy, or safety-relevant systems is advantageous
• Experience with nonlinear optimization, factor graphs, or smoothing is advantageous
• Knowledge of GNSS, inertial sensing, lidar, sensor timing, calibration, and real-world failure modes is advantageous
• Experience with lidar localization, ICP, continuous-time estimation, or articulated-machine estimation is advantageous
• Experience building offline reference estimators or independent ground-truth systems is advantageous
• Production experience with Rust is advantageous
• Familiarity with construction, mining, agricultural, or other heavy industrial machines is advantageous

Core Competencies

Demonstrates expertise in developing state-estimation systems and localization algorithms for autonomous machines, with strong foundations in probabilistic estimation, linear algebra, and sensor fusion. Proficient in debugging and data analysis across algorithms, software, and hardware to enhance system reliability and performance.

Highest-signal resume keywords

• State Estimation
• Localization Algorithms
• GNSS/INS Fusion
• Rust Programming
• Kalman Filtering

Hard Skills

• State Estimation
• Localization
• Sensor Fusion
• Probabilistic Estimation
• Linear Algebra
• 3D Geometry
• Numerical Methods
• Kalman Filtering
• Lidar Calibration
• Nonlinear Optimization

Soft Skills

• Debugging
• Data Analysis
• Collaboration

Industry Keywords

• Autonomous Vehicles
• Robotics
• Heavy Industrial Machines
• Construction
• Mining

Tools & Technologies

• GNSS
• IMU
• Lidar
• Simulation
• Embedded Platforms