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Foster City, California, United States
Onsite
Zoox is on an ambitious journey to develop a full-stack autonomous mobility solution for cities and safely deploy such a robotaxi solution. The System Design and Mission Assurance (SDMA) team plays a foundational role in the company's success, responsible for constructing the safety case and fail-operational design for our autonomous driving robots before public road deployment. You will be part of an organization with strong leadership and a transparent, respectful culture that enables you to reach your full potential.
We are looking for a Senior Systems Engineer to drive the technical evolution of the Fail Operations metrics, frameworks, and processes. In this role, you will lead the refinement of how Zoox categorizes, estimates, and tracks autonomous driving performance events, working closely with cross-functional partners across Data Science, SDMA, Software and Operations. You will serve as a key technical partner to SDMA’s metrics leadership, shaping the methodology that underpins Zoox’s assessment of readiness to scale.
Own and evolve the core Fail Operational metric framework for quantifying, severity-ranking, and systematically driving down autonomous-mission stoppage and degradation events, including category definitions, classification methodology, and triage criteria used to identify and assess mission-critical events across all driving behavior domains
Lead Fail Operational metric target-setting for new and existing milestones, authoring supporting documentation and consolidating inputs across metric categories to assess overall readiness for milestone closure
Drive the evolution of the Fail Operational metric architecture, ensuring alignment with current priorities and operational needs
Develop process for reviewing observed events, mapping to seen failure modes or confirming as new, and integrating those observations into estimations to drive business priorities.
Partner cross-functionally with Software, Hardware, and Operations teams to escalate issues, identify mitigations, evaluate emerging risks from testing pipelines, and support delivery of features that improve performance metrics
Communicate complex metric concepts, data analyses, and actionable insights to diverse stakeholders and executives, translating technical findings into clear recommendations that inform decision-making
B.S. or higher degree in Systems Engineering, Computer Science, Electrical Engineering, Applied Mathematics, or a related field
5+ years of relevant professional experience in systems engineering, data analysis, performance tracking, risk quantification, or fault management for complex and safety-critical systems
Demonstrated experience defining, implementing, and managing quantitative metrics and data-driven frameworks, with proficiency in probability, statistics, and Python for large-scale data analysis
Strong understanding of fault detection, categorization, and severity assessment methodologies, with experience developing technical frameworks, taxonomies, or classification systems
Excellent technical communication and documentation abilities, with a collaborative approach to influencing, driving consensus, and leading cross-functional initiatives
M.S. or Ph.D. in Engineering, Computer Science, or a related field
Systems engineering or system safety experience with autonomous driving, robotics, or fleet-scale vehicle operations
Experience with fail-operational design, fault tolerance, or fault management in safety-critical domains, including familiarity with hazard analysis methods such as STPA, FTA, FMEA, or FHA
Metrics ownership experience and knowledge of industry safety standards such as ISO 26262, ISO 21448, MIL-STD-882
Experience building processes from conception to implementation at scale