Sensing and Perception System Safety Engineer (Autonomous Vehicles)

Location: Foster City, California, United States; hybrid workplace

Company

Zoox is developing a full-stack autonomous mobility solution and robotaxi platform for urban environments.

What you will do

• Define safety requirements and metrics for camera, lidar, radar, sensor fusion, and ML-based perception subsystems.
• Lead cross-functional technical projects with Software, Hardware, Operations, Data Science, and V&V teams to support safety arguments.
• Design safety mechanisms using ISO 26262, including HARAs and Functional Safety Concepts, and apply SOTIF principles.
• Develop safe, fail-operational, cost-optimized sensing architectures and guide next-generation sensor selection.
• Analyze field and simulation data to identify root causes, determine next steps, and validate assumptions.
• Use AI and LLM tools to accelerate analysis and automate repetitive processes.

Requirements

• BS or MS in a related technical field such as Electrical/Electronics Engineering, Computer Engineering, Mechanical Engineering, Computer Science, Robotics, or Mechatronics.
• Experience as a Design or Systems Engineer for complex or mission-critical systems with high levels of fail-operational redundancy, especially in sensing and perception.
• 3+ years of hands-on systems, safety, or related engineering experience focused on safety-critical, high-integrity systems in Automotive, ADAS, Autonomous Vehicles, Aerospace, or Robotics.
• Effective communication and collaboration skills, including the ability to explain complex technical concepts to technical and non-technical stakeholders.

Nice to have

• Experience with sensing hardware, its physics, limitations, and tradeoffs in safety-critical and fail-operational systems.
• Experience applying ISO 26262 and ISO 21448 SOTIF to L2+ ADAS and autonomous vehicles, including hazard analysis, functional decomposition, validation, and verification.
• Experience with Python and/or Databricks for data mining, analysis, and visualization.
• Strong analytical skills in performance-metric definition and system-level trade-off analysis.
• Understanding of modern perception stacks, ML/AI systems, their requirements, and integration challenges.
• Experience with requirements-management tools such as Polarion, DOORS, or Jama; Polarion is preferred.