Design Reliability Engineer – Sensor, Compute and EE Systems

zoox

4100

Foster City, CA, USA

Posted on: 2026-01-26

Category: emobility

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Employment type:

Full time

Experience required:

Intermediate

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.

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 leading engineers with diverse backgrounds, such as robotics, control, and vehicle engineering, to deliver vehicle performance using virtual tools and methodologies. In taking on the virtual and physical durability development, you will work on predicting where the vehicle is within its lifespan and providing maintenance scenarios and optimization strategies.

About Zoox

Zoox 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.

Accommodations

If 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.

In this role, you will:

Establish and refine the system/component-level targets for reliability performance of the sensors (including LiDAR, radar, and camera components), AI compute system, and other automotive electronic control units (ECU) in collaboration with internal stakeholders on the Hardware and Sensors Engineering teams.

Drive the design failure mode and effects analysis process (DFMEA) for relevant sensors, high-performance computers, and ECUs to capture key reliability risks and define appropriate mitigation strategies.

Use reliability targets, DFMEA outputs, and physics-of-failure principles to partner with validation engineers in developing virtual and physical test plans that prove out designs and demonstrate required reliability performance.

Lead the definition and deployment of Prognostics and Health Monitoring (PHM) strategies for sensors, compute, and EE systems, including identification of available signals, development of health indicators, degradation models, and failure precursors to enable early fault detection and remaining useful life estimation

Partner with software, data, and systems teams to operationalize PHM capabilities in the vehicle and backend pipelines, translating reliability risks into actionable monitoring, alerting, and maintenance recommendations.

Pave the way from development to field deployment by building closed-loop reliability systems that leverage field data, PHM insights, and fleet telemetry to identify performance improvement opportunities and drive corrective actions across design, validation, and operations.

Qualifications

Bachelor's and/or Master’s-level engineering degree or equivalent technical background with 3-5 years of hands-on experience in Reliability Engineering.

Detailed understanding of sensors, high-performance computers, and ECUs, including common failure modes and associated validation methodologies.

Expertise in reliability data analysis, risk assessment, and development of component reliability targets aligned with functional safety and business objectives.

Strong foundation in reliability statistics (e.g., Weibull, life data analysis, degradation modeling, confidence bounds) and reliability physics (e.g., thermal, vibration, electrical, and environmental failure mechanisms).

Experience in failure mode assessment, accelerated reliability testing, advanced field reliability monitoring, and/or prognostics and health management concepts.

Personable, with the ability to lead and influence cross-functional engineering teams toward world-class reliability and dependability.