Base: $195,000 - $230,000; bonus/equity: not speci...
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State estimation frameworks like factor graphs
Sensor fusion of cameras lidar radar gnss imu
Modern c++ programming in linux environment
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May Mobility is seeking a Staff Autonomy Engineer specializing in Localization to lead the development of high-performance localization systems for autonomous vehicles. The ideal candidate will possess advanced expertise in state estimation, sensor fusion, and C++ programming, along with significant industry experience.
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Job Summary
May Mobility is transforming cities through autonomous technology to create a safer, greener, and more accessible world.
The role requires owning the localization integrity and safety strategy with sophisticated fault detection mechanisms.
Benefits include comprehensive healthcare, generous paid parental leave, and a flexible vacation policy.
Matching Summary
Match Score: 75
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May Mobility is seeking a Staff Autonomy Engineer specializing in Localization to lead the development of high-performance localization systems for autonomous vehicles. The ideal candidate will possess advanced expertise in state estimation, sensor fusion, and C++ programming, along with significant industry experience.
**
Salary
Base: $195,000 - $230,000; Bonus/Equity: Not specified; Benefits: Comprehensive healthcare suite including medical dental vision life disability plans
Skills & Requirements
Must-have
State estimation frameworks like Factor Graphs
Sensor fusion of Cameras LiDAR Radar GNSS IMU
Modern C++ programming in Linux environment
Real-time performance optimization for AV systems
Safety-critical system architecture design
Nice-to-have
Deep-learning based localization features
Vehicle dynamics modeling expertise
Patents or publications in robotics conferences
Large-scale SLAM experience in urban environments
Wheel odometry calibration skills
Key Requirements
Ph.D. or Master's degree in Robotics or related field
10+ years industry experience in localization systems
5+ years in lead or staff technical role
Expertise in probabilistic robotics and Kalman filtering