Sr. Electrical Integration Engineer - Diagnostics

Zoox•Foster City, CA

3d•$204,000 - $280,000

About The Position

In this role, you will own diagnostic deployment for the current service vehicle fleet and successor platforms, from requirement definition through release into the operating fleet, and foster design for diagnostics with system, firmware, and software teams. You will improve diagnostic quality to reduce time-to-diagnose in the fleet, drive fault isolation accuracy and resolution so a triggered fault points to the right component and repair activity. You will close end-to-end diagnostic gaps from requirement through V&V, own the diagnostic requirements set, maintain traceability between requirements, implementation, test coverage, and in-fleet performance, and lead design and test reviews to catch gaps early. You will define and deploy service actions tied to diagnostic outcomes, partner with service engineering and fleet operations to ensure each fault maps to an actionable, verified repair, and confirm effectiveness using fleet data. You will identify and develop prognostic features that predict component and system issues ahead of failure, translating fleet telemetry into monitoring strategies that reduce unplanned downtime, and report diagnostic health and gap closure status to cross-functional and program leadership. You will develop metrics to measure diagnostic success and use them to identify system and process gaps, driving continuous improvement across the diagnostic lifecycle.

Requirements

Bachelor's or Master's of Science in Electrical, Mechanical, Systems, or Computer Engineering.
10+ years of experience in vehicle or system diagnostics, with direct experience supporting a production or operating fleet.
Demonstrated experience improving diagnostic quality and fault isolation accuracy using field data, with measurable reduction in time-to-diagnose.
Working knowledge of automotive serial communication protocols (CAN, CAN-FD, LIN, Automotive Ethernet) and diagnostic protocols and standards (UDS/ISO 14229, OBD, DTC management).
Experience with fail-operational and fail-safe concepts and system diagnostics under a functional safety standard (ISO 26262 or equivalent).
Hands-on data analysis skills – able to query, process, and draw conclusions from large fleet datasets (Python, SQL, or equivalent).
Experience defining service and repair procedures and working directly with service or field operations teams.

Nice To Haves

Experience developing prognostics, predictive maintenance, or condition monitoring features for vehicles or other fleets of complex hardware.
Experience applying statistical or machine learning methods to fault detection and anomaly detection at fleet scale.
Experience with over-the-air software and calibration deployment to a vehicle fleet.
Familiarity with Model-Based System Design (MBSD) processes.

Responsibilities

Own diagnostic deployment for the current service vehicle fleet and successor platforms, from requirement definition through release into the operating fleet, and foster design for diagnostics with system, firmware, and software teams.
Improve diagnostic quality to reduce time-to-diagnose in the fleet. Drive fault isolation accuracy and resolution so a triggered fault points to the right component and repair activity.
Close end-to-end diagnostic gaps from requirement through V&V. Own the diagnostic requirements set, maintain traceability between requirements, implementation, test coverage, and in-fleet performance, and lead design and test reviews to catch gaps early.
Define and deploy service actions tied to diagnostic outcomes. Partner with service engineering and fleet operations to ensure each fault maps to an actionable, verified repair, and confirm effectiveness using fleet data.
Identify and develop prognostic features that predict component and system issues ahead of failure, translating fleet telemetry into monitoring strategies that reduce unplanned downtime, and report diagnostic health and gap closure status to cross-functional and program leadership.
Develop metrics to measure diagnostic success and use them to identify system and process gaps, driving continuous improvement across the diagnostic lifecycle.