Senior / Staff Software Engineer, Localization

The Localization team at Waabi is responsible for answering one of the most critical questions in autonomous driving: exactly where is the vehicle right now? As a Senior or Staff Software Engineer on the Localization team, you will be a domain expert architecting the highly precise, robust state estimation systems that keep our robotaxis and 80,000lb trucks safely on the road. You will design algorithms that seamlessly fuse data across a complex sensor suite to provide real-time, centimeter-accurate pose estimation, even in degraded or GPS-denied environments. You will collaborate with world-renowned engineers and scientists to merge traditional robotics state estimation with Waabi's AI-first approach.

You will...

- Act as a deep domain expert in state estimation, pushing the boundaries of what is possible in real-time vehicle localization.

- Design, implement, and optimize robust algorithms for multi-sensor fusion leveraging IMU, LiDAR, Radar, Camera, GNSS, wheel encoders, etc.

- Architect and develop mathematical models to be used in factor graph optimization, Kalman filters, etc.

- Develop highly optimized, low-latency Rust code that runs directly on the vehicle's various compute devices in real-time.

- Partner with the Perception and Mapping teams to tightly couple map data and semantic landmarks into the localization pipeline.

- Build rigorous evaluation frameworks to measure localization accuracy, integrity, fault tolerance across millions of miles in Waabi World (our simulation platform) and on physical test tracks.

Qualifications:

- BS, MS, or PhD in Robotics, Computer Science, Aerospace/Electrical Engineering, or related field, with a minimum for 5 years of industry experience.

- Deep, rigorous domain expertise in probabilistic robotics, state estimation, and 3D geometry (Gaussian estimation, filtering, smoothing, and mapping).

- Proven experience building and optimizing online and/or offline Simultaneous Localization and Mapping (SLAM) systems, including deep knowledge of point-cloud registration algorithms (e.g. ICP).

- Extensive hands-on experience processing and fusing data from physical sensors (IMU, LiDAR, Radar, GNSS, etc.).

- Exceptional systems-level programming skills in modern C++ and/or Rust, with a strong understanding of memory management, concurrency, and real-time computing constraints.

- Proficiency in python for data analysis, prototyping, and tooling.

- Strong mathematical foundation in linear algebra, calculus, and probability theory.

- A proven track record of deploying complex state estimation algorithms onto physical robots or autonomous vehicles operating in the real world.

Bonus/nice to have:

- Familiarity with industry-standard optimization libraries (e.g., GTSAM, Ceres Solver, g2o).

- Experience with "learned localization" - applying deep learning and AI/ML models to improve traditional state estimation and feature matching.

- Experience with high-speed highway autonomous driving constraints.