Compute Platform System Safety Engineer

zoox

4100

Foster City, CA, USA

Posted on: 2026-01-02

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.

Zoox is on an ambitious journey to develop a full-stack autonomous mobility solution for cities and deploy such a robotaxi solution safely and reliably. We are seeking a System Safety Engineer to perform safety analyses of complex electronic and software-based-systems, specifically high performance compute. The ideal candidate will be on the Zoox's System Design and Mission Assurance (SDMA) team to identify opportunities to improve, adapt, and generally refine our safety concept, safety mechanisms to detect and mitigate hardware failures, and residual risk assessments, ensuring the safe deployment of autonomous driving technology.

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:

Execute and own the output of the Compute Safety Analysis (FMEDA) for various compute platforms for each milestone

Respond to and aid in Root Cause Analysis (RCA) for safety-related Compute Platform field failures

Collaborate with partner teams to improve diagnostic coverage against single point and multiple point latent failures on our existing hardware platform.

Work with other SDMA engineers to ensure requirements are well captured and structured to account for runtime and latent failures in the sensing, perception and compute path

Perform functional safety analysis to ensure the safety concept remains compatible with the core objectives of ISO 26262

Work with partner teams to develop safety- and cost-optimized, next-generation compute architectures. Guide the selection of next-generation compute and related hardware.

Lead cross-functional technical projects, including interactions with teams such as Software, Hardware, Operations, Data Science, V&V to ensure we have the appropriate data to support our arguments and solutions that can meet our requirements

Qualifications

BS or MS in a related technical field, such as Electrical/Electronics Engineering, Computer Engineering, Mechanical Engineering, Computer Science, Robotics, Mechatronics, etc.

Experience as a Design or Systems Engineer for complex or mission-critical systems with high levels of fail-operational redundancy

3+ years of hands-on systems, safety, or related engineering experience with a focus on analysis of safety critical high-integrity systems in Automotive, ADAS, Autonomous vehicles, Aerospace or Robotics industries

Effective communication and collaboration skills, with the ability to articulate complex technical concepts to both technical and non-technical stakeholders.

Bonus Qualifications

PhD in a related technical field

Experience in the application of ISO 26262 (Functional Safety) and ISO 21448 (SOTIF) to L2/L3/L4/L5 ADAS and autonomous vehicles

Experience with FMEDA or FMEA for complete safety critical systems

Experience with hazard analysis, functional decomposition, validation, and verificationExperience in systems with multiple layers of redundancies (including but not limited to SIL 4 / DAL A)

Experience with simulation and modeling of physical hardware/software systems or data-driven modeling and analysis techniques

A reliability modeling background including the analysis of field data

Experience using requirements management tools such as Polarion (preferred), DOORS or Jama

Experience with Python and/or Databricks for data analysis and visualization

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