Platform Systems Engineer; Sensing and Perception, Maps and Localization
About the role
Platform Systems Engineer focused on Sensing, Perception, Maps, and Localization within Waabi's Platform team. On-site role across multiple locations (Phoenix, AZ; San Francisco, CA; Pittsburgh, PA) requiring end-to-end systems engineering, cross-functional collaboration, and safety-focused development for autonomous vehicle sensing and localization pipelines.
Responsibilities
- Drive Technical Execution: Lead the end-to-end systems engineering lifecycle for the Sensing, Perception, Maps, and Localization domains, ensuring timely delivery of robust solutions across hardware and software teams.
- Architect Requirements: Create and refine Autonomous Vehicle (AV) Requirements using analytical and numerical methods, focusing on sensing capabilities, perception performance, sensor fusion, mapping, and pose estimation.
- Own the Contract: Own the definition and requirements development of the Sensing, Perception, and Localization contracts, covering sensor performance, calibration, data quality, and system degradation strategies.
- Lead Cross-Functional Integration: Act as the primary technical liaison connecting AI and software engineers, hardware engineers, and safety teams to resolve complex system-level bottlenecks and build consensus on architectural trade-offs.
- Validate via Data: Create methods and use physical and simulated data to inform and verify principled requirements for the entire sensor suite and localization pipeline.
- Advance Simulation: Improve the simulation and synthetic data generation of sensor models for AVs.
- Build the Safety Case: Directly contribute to the system safety case by mapping high-level safety goals to deployed architecture, ensuring traceability from requirements through to verification and validation (V&V).
- Elevate the Team: Mentor junior and mid-level engineers, fostering a culture of rigorous systems engineering, proactive risk management, and flawless execution within the Platform team.
Qualifications
- 3+ years of industry experience in autonomous vehicles, robotics, or aerospace, with a proven track record of taking complex autonomous systems from R&D to deployment.
- Strong foundation in AV systems, specifically in sensing (Lidar, Radar, Camera), perception algorithms, sensor fusion, mapping, and localization (e.g., GNSS/INS, SLAM, odometry).
- Technical Breadth: Deep knowledge of sensor physics, signal processing, data acquisition/management, and dealing with correlated system errors.
- Systems Rigor: Expert knowledge of Systems Engineering and Verification & Validation (V&V) best practices, including requirements decomposition from high-level safety goals into detailed, verifiable functional and technical specs for Level 4 AV systems.
- Safety Standards: Working knowledge of functional safety standards (e.g., ISO 26262) and translating probabilistic safety goals into physical, quantifiable metrics.
- Programming: Comprehensive coding skills in Python, C++, or other common programming languages used for data analysis and systems modeling.
- Simulation & Modeling: Extensive experience in sensor simulation, error modeling, and perception/localization requirements development.
- Communication: Exceptional communication and stakeholder management skills, with the ability to distill complex technical risks into actionable decisions for leadership.
Skills
Benefits
- Competitive compensation and equity awards.
- Health and Wellness benefits encompassing Medical, Dental and Vision coverage (for full-time employees only).
- Unlimited Vacation.
- Flexible hours and Work from Home support.
- Daily drinks, snacks and catered meals (when in office).
- Regularly scheduled team building activities and social events both on-site, off-site & virtually.
About Waabi
pioneering Physical AI, starting with autonomous trucks.
Waabi is pioneering Physical AI, starting with autonomous trucks. We developed a next-generation approach leveraging an end-to-end interpretable and verifiable AI model that’s powered by the industry's most realistic neural simulator. This dramatically reduces the development time and resources needed to bring self-driving vehicles to public roads — safely and at scale.
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