Senior Software Engineer, Localization – Pose Estimation (Hybrid)

Aurora; Mountain View (CA); Hybrid; USD 162,000 - 260,000; Full time

Benefits offered by this job

Hybrid work model

Equity compensation

Annual bonus

Job summary

Aurora is seeking a Senior Software Engineer to advance localization for its self-driving fleet. You will design and implement solutions to estimate vehicle and asset pose, and rigorously test them for safety and efficiency.

Collaboration with cross-functional teams will drive critical Aurora product goals. Candidates should have 5+ years in software, strong C++/Python skills, and a graduate CS/Robotics/EE degree with expertise in state estimation, sensor fusion, and SLAM.

Qualifications

• 5+ years of industry experience building software in a production environment.
• Proficient in C++ and Python using modern best practices.
• Graduate level degree in CS/Robotics/EE.
• Deep knowledge of state estimation theory and practice (sensor fusion, Kalman Filtering, non-linear estimation, SLAM).
• Experience in estimation and modeling with sensor data (lidar, IMU, radar, camera).
• Deep understanding in spatial transforms, linear algebra, probabilistic estimation.

Responsibilities

• Design, implement, and maintain solutions for estimating the pose of vehicles and other assets, such as trailers.
• Rigorously evaluate and test solutions to verify safety and efficiency of the localization system.
• Collaborate with engineers and stakeholders on partner teams to solve problems of high importance to Aurora products.

Job description

Aurora is seeking a Senior Software Engineer to advance localization for its self-driving fleet. You will design and implement solutions to estimate vehicle and asset pose, and rigorously test them for safety and efficiency.

Collaboration with cross-functional teams will drive critical Aurora product goals. Candidates should have 5+ years in software, strong C++/Python skills, and a graduate CS/Robotics/EE degree with expertise in state estimation, sensor fusion, and SLAM.