Meet the team:

The Glydways perception team is responsible for designing and implementing a perception system that includes data fusion from state-of-the-art sensors (e.g., LIDAR, RADAR, High definition cameras, Ultra-wide-band radios, etc.) and robust detection, classification, and tracking of any and all obstacles that could present a hazard to the vehicle (Glydcars) in the system. The perception system for Glydways will reason about information from each Glydcar and from regularly spaced sensor pods monitoring the road network.  

The perception team plays a vital role within the Autonomy Software engineering team.  The team’s deliverables include: 

1. Documenting a detailed design for enacting a safe system that can be certified by public transportation authorities.
2. Implementing said design on mature prototype vehicles in demonstrations to customers, potential customers, and investors.
3. Expanding the design to include fail-operational capabilities that extend the overall system to safely give our customers a more comfortable experience.
4. Managing data collection, autonomy testing, and milestone demonstration events that showcase the system’s maturing capabilities, leading to a production system.  

Team members may work remotely and must be self-motivated.  

 

Roles & Responsibilities:

• Design, implement, and maintain high-performance C++ modules at the boundary of detection like tracking, and prediction.
• Integrate outputs from multiple sensors(camera, lidar, radar, map) into EKF-based tracking and fusion systems.
• Own metrics, evaluation pipelines, and tooling to measure detection and tracking quality and catch regressions at scale.
• Define and maintain clear interfaces between perception, tracking, and planning modules with a focus on robustness and debuggability.
• Develop simulation, log-replay, visualization, and offline analysis workflows to improve test coverage before on-vehicle deployment.

 

Knowledge, Skills and Abilities:

• Strong proficiency in modern C++ (C++14/17 or newer).
• Production experience with state estimation and multi-sensor fusion, including EKF/UKF, motion models, data association, and uncertainty handling.
• Experience designing metrics and evaluation frameworks for real-time, ML-driven robotics systems.
• Strong debugging skills across distributed and asynchronous pipelines, using logs and metrics to drive root-cause analysis.
• Excellent verbal and written communication skills.