Sr. Staff Systems Engineer, Perception-Planner Risk
Core
Define quantitative safety risk analysis approaches for sensing and perception systems, design statistical models for evaluating end-to-end performance, and prototype workflows to estimate exposure of events relevant to perception-driven behavioral risk.
Role type
Sr. Staff Systems Engineer (Perception-Planner Risk)
Builds
Quantitative risk assessment methodologies, statistical models for sensor suite evaluation, and risk estimation workflows for autonomous driving systems.
Domain
Autonomous driving, vehicular robotics, safety-critical systems
Deliverable
production ML models
Required skills
Quantitative risk estimation, statistical modeling, experimental design, systems engineering fundamentals, Python, C++, vehicular robotics, state-of-the-art ML techniques
Preferred skills
Autonomy driving industry experience, large-scale infrastructure testing, model-driven metrics development
Technologies
Python, C++, simulators, sensors-in-loop
Responsibilities
Design and implement quantitative methods for evaluating end-to-end performance; analyze rare events with scarce operational data; support trade studies for perception hardware/software architecture; improve quantitative rigor and standardization of risk reporting; collaborate with Onboard Software, Test Engineering, and Systems Safety teams.
Seniority
Sr. Staff, hands-on IC with leadership accountability