Senior/Staff Systems Engineer - Autonomy System Performance

Zoox

2600

Foster City, CA, United States

Posted on: 2025-06-30

Category: emobility

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Employment type:

Full time

Experience required:

Senior

Salary

Salary not provided

About the company:

Zoox is transforming mobility-as-a-service by developing a fully autonomous, purpose-built fleet designed for AI to drive and humans to enjoy.

Zoox is on an ambitious journey to develop a full-stack autonomous mobility solution for cities and deploy such a robotaxi solution safely. As a Senior/Staff Systems Engineer focusing on autonomy system service metrics at Zoox, you will have the opportunity to work closely with cross-functional teams to define, develop, and continuously refine the methodology for measuring the service and driving performance of our autonomy system. Your work will be critical in informing key launch decisions and ensuring the successful deployment of Level 5 autonomous driving technology by identifying and quantifying events that impact the robotaxi’s ability to safely complete riders' journeys.

In this role, you will:

Lead the definition, development, and evolution of progress metrics that measure the robotaxi’s ability to safely complete customers’ journeysDevelop robust methodologies for quantifying the readiness and maturity of the autonomous driving system against defined progress metrics.

Model the performance impact of autonomy behavior and residual operational risks.

Perform in-depth system analysis to derive comprehensive verification and validation (V&V) strategies for progress metrics.

Communicate complex metric concepts, model outcomes, and actionable insights to diverse stakeholders and executives.

Ensure end-to-end traceability of metrics to strategic goals and system performance targets, enabling continuous feedback loops.

Qualifications:

M.S. or higher degree in an Engineering or Computer Science discipline

At least 7 years of relevant professional experience in systems engineering, data analysis, performance tracking, or risk quantification for complex systems.

Demonstrated experience in defining, implementing, and managing quantitative metrics and data pipelines for software or hardware systems.

Proficiency in quantitative analysis/modeling tools and ability to use Python to interface with large-scale driving and simulation data sources.

Strong understanding of complex software systems, preferably in robotics, autonomous driving, or aerospace.

Collaborative team player with good written and in-person communication skills, capable of influencing, driving consensus, and presenting complex data to varied audiences including senior executives.