State Estimation and Navigation Engineer
About the role
Archer is an aerospace company based in San Jose, California building an all-electric vertical takeoff and landing aircraft with a mission to advance the benefits of sustainable air mobility. We are designing, manufacturing, and operating an all-electric aircraft that can carry four passengers while producing minimal noise. Our sights are set high and our problems are hard, and we believe that diversity in the workplace is what makes us smarter, drives better insights, and will ultimately lift us all to success. We are dedicated to cultivating an equitable and inclusive environment that embraces our differences, and supports and celebrates all of our team members.
This role must be based onsite in the United States. Visa sponsorship is not available for this position.
Responsibilities
- Develop and tune state-estimation algorithms for GPS-denied and GNSS-degraded navigation
- Implement visual-inertial odometry (VIO), lidar/vision-aided INS, and multi-sensor fusion approaches
- Integrate state-estimation solutions with IMU, camera, lidar, and other onboard sensors
- Validate navigation performance through simulation, bench testing, and field testing
- Analyze test data to identify and resolve navigation performance issues
- Collaborate with perception, controls, and test teams to ensure robust navigation across a range of operating conditions
Requirements
- Background in GN&C, robotics, or a related technical field
- Strong proficiency in C++ and Python
- Experience with VIO/SLAM techniques
- Experience with EKF or factor-graph-based sensor fusion
- Experience integrating IMU, camera, and lidar sensors into a navigation stack
Qualifications
- Experience with PX4 or ArduPilot EKF
- Hands-on experience with GPS-denied navigation testing
- Background in subscale aircraft or robotics navigation
Pay
For this position we are targeting a base pay between $140,000 - $260,000. Actual compensation offered will be determined by factors such as job-related knowledge, skills, and experience.