Senior Reliability Engineer - EV Powertrain Systems

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Zoox seeks a Senior Reliability Engineer for EV powertrain in Foster City, onsite. You will set reliability targets for EDU, HVB and HV harnesses, lead DFMEA, translate risk insights into validation plans, define a PHM strategy, and drive field reliability initiatives across design, validation and operations while collaborating with suppliers and cross-functional teams to bake durability into architecture. A Master’s degree and 10+ years in reliability, deep EV EDU/HVB knowledge, strong data analysis and risk assessment skills, and a first principles mindset with leadership are required. Bonus: CRE, ISO 26262 familiarity, SQL/Python. To apply, quantify impact and DFMEA/PHM successes, show leadership, and demonstrate startup-ready collaboration.

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At Zoox, we have set the goal to provide our customers with the highest level of safety and a best-in-class experience while using our fully autonomous vehicles. You will work with a team of world-class engineers with diverse backgrounds, such as robotics, control, and vehicle engineering, to deliver vehicle performance using advanced virtual tools and methodologies. In taking on the virtual and physical durability development, you will predict where the vehicle is within its lifecycle and define maintenance, monitoring, and optimization strategies. Working in a startup environment gives you the chance to lead technically, influence system design, and make a meaningful impact on the final product.

In this role, you will:

• Establish and refine system- and component-level reliability targets for the electric drive unit (EDU), high-voltage battery (HVB), and HV to LV Power Distribution (DCDC and HV harnesses) in collaboration with Vehicle Systems Engineering and cross-functional stakeholders
• Drive the design failure mode and effects analysis (DFMEA) process for EDU and HVB to identify critical reliability risks and define effective mitigation strategies
• Apply reliability targets, DFMEA risk insights, and physics-of-failure understanding to develop virtual and physical validation plans in partnership with validation engineers
• Lead the definition of Prognostics & Health Monitoring (PHM) strategy for EDU and HVB systems, including field monitoring concepts that enable early detection, return-to-base actions, and reduced roadside events
• Support execution of PHM and field reliability initiatives by translating design-time assumptions into measurable signals, metrics, and feedback loops that inform corrective actions and design improvements
• Pave the way from development to field deployment by building systems and processes that identify reliability performance gaps, prioritize improvement opportunities, and drive timely corrective actions across design, validation, and operations
• Contribute to broader design reliability efforts, ensuring durability, serviceability, and lifecycle reliability considerations are embedded early in system architecture and design decisions
• Engage with component suppliers to ensure components are able to achieve our high reliability standards

Qualifications:

• Master's-level engineering or similar technical degree with 10+ years of hands-on experience in Reliability Engineering
• Detailed understanding of EV EDU and HVB systems, and typical failure modes and test methods for these systems
• Deep understanding of reliability data analysis and risk assessment, and how to develop component reliability targets based on functional safety and business objectives
• Experience in failure mode assessment, accelerated reliability testing, and advanced field reliability monitoring concepts
• Strong first principles mindset with an understanding of governing equations for both acceleration models and powertrain component theory of operation
• Personable with the ability to lead and coach a high-caliber engineering team toward world-class levels of reliability/dependability

Bonus Qualifications:

• ASQ Certified Reliability Engineer, or similar professional recognition
• An understanding of ISO 26262 Functional Safety
• Working knowledge of SQL, Pyspark, and python based packages  for fleet wide data analysis
• Experience applying numerical methods to highly distributed compute workloads
• Familiarity with lumped element models for mechanical or thermal analysis

About ZooxZoox is developing the first ground-up, fully autonomous vehicle fleet and the supporting ecosystem required to bring this technology to market. Sitting at the intersection of robotics, machine learning, and design, Zoox aims to provide the next generation of mobility-as-a-service in urban environments. We’re looking for top talent that shares our passion and wants to be part of a fast-moving and highly execution-oriented team.
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AccommodationsIf you need an accommodation to participate in the application or interview process please reach out to [email protected] or your assigned recruiter.
A Final Note:You do not need to match every listed expectation to apply for this position. Here at Zoox, we know that diverse perspectives foster the innovation we need to be successful, and we are committed to building a team that encompasses a variety of backgrounds, experiences, and skills.