bluedoor data·Job Postings API·bluedoor.sh ↗

HomeCompaniesZooxDesign Reliability Engineer – Sensor, Compute and EE Systems

Design Reliability Engineer – Sensor, Compute and EE Systems

Zoox · Foster City, CA · Hybrid · Active · $164,000–$197,000 / year · Lever

Job facts

FieldValue
CompanyZoox
TitleDesign Reliability Engineer – Sensor, Compute and EE Systems
Normalized title-
Department / teamSupply Chain Quality and Reliability / Quality and Reliability
LocationFoster City, CA, United States
Work modelHybrid / Hybrid
Employment typeFull Time
Salary$164,000–$197,000 / year
Statusactive
ATS providerLever
Posted / first seen2026-01-26 / 2026-05-29
Changed / last seen2026-05-29 / 2026-06-06

Related slices

PageWhat it containsOpen
Company jobsActive postings from Zoox.Open
Company breakdownsRole, location, ATS, and work model facets for this company.Open
ATS provider jobsActive postings observed through Lever.Open
Provider filtered searchThe same provider as a filtered job collection.Open
City jobsActive postings in Foster City.Open
Department jobsActive postings in Supply Chain Quality and Reliability.Open
Work model jobsActive Hybrid postings.Open
Lifecycle eventsOpen, update, close, and reopen events for this posting.Open
Original postingCanonical source or apply URL captured from the ATS.Open

Linked records

CompanyZoox
Source45f1a12e-419b-4b96-93be-f479c9356a1b
ATS providerLever

Description

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. Follow us on LinkedIn 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. Bonus Qualifications Demonstrated knowledge in Python-based data analysis tools such as PySpark, Pandas, NumPy, and SciPy. ASQ Certified Reliability Engineer, or similar professional recognition An understanding of ISO 26262 Functional Safety

Full job record

Job IDaa1f710d2463f7389ded564ee14b6da33455381e
Org ID518be277-8ec5-4735-b0ad-193a2bc397c7
Source ID45f1a12e-419b-4b96-93be-f479c9356a1b
Board ID45f1a12e-419b-4b96-93be-f479c9356a1b
Providerlever
Provider Job Key63829003-24ba-4169-96a6-a3349b68bf17
TitleDesign Reliability Engineer – Sensor, Compute and EE Systems
Normalized Title
Statusactive
Activeyes
Location TextFoster City, CA
DepartmentSupply Chain Quality and Reliability
TeamQuality and Reliability
Employment TypeFull-time
Workplace Typehybrid
Remote Policyhybrid
CountryUnited States
RegionCA
CityFoster City
Salary RawUSD 164000-197000 per-year-salary
Salary Min164,000
Salary Max197,000
Salary CurrencyUSD
Salary Periodyear
Source URLhttps://jobs.lever.co/zoox/63829003-24ba-4169-96a6-a3349b68bf17
Apply URLhttps://jobs.lever.co/zoox/63829003-24ba-4169-96a6-a3349b68bf17/apply
First Seen At2026-05-29 06:58:06Z
Last Seen At2026-06-06 20:04:34Z
Last Checked At2026-06-06 20:04:34Z
Last Changed At2026-05-29 06:58:06Z
Inactive At
Source Posted At2026-01-26 20:03:44Z
Source Updated At
Raw Payload Uris3://job-postings-prod-raw-590183727216/raw/provider=lever/board=zoox/date=2026-06-06/2026-06-06T20-04-33-960Z-dbc899b7b70bd68deef4fecc07510b625903b1c9c1b990b1843279904e7d9bc6.json
Event Fields
{
  "content_hash": "829aebea7ec75e077462ce7af4afb6eb7c17e13d88c71db1c11a48e77e15605d",
  "source_hash": "6850e50ad79fd3813855067c3dd639a05faae9fe194479e5664d1b7ca744612a",
  "last_changed_at": "2026-05-29T06:58:06.279Z",
  "active_status": "active"
}
Parsed Structured
{
  "language": "en",
  "location": {
    "raw": "Foster City, CA",
    "city": "Foster City",
    "region": "CA",
    "country": "United States",
    "is_remote": false,
    "confidence": 0.9
  },
  "salary_max": 197000,
  "salary_min": 164000,
  "inferred_at": "2026-06-06T20:04:34.758Z",
  "launch_scope": {
    "reason": "english_us_canada",
    "included": true,
    "language": "en",
    "location": {
      "raw": "Foster City, CA",
      "city": "Foster City",
      "region": "CA",
      "country": "United States",
      "is_remote": false,
      "confidence": 0.9
    },
    "countries": [
      "United States"
    ]
  },
  "remote_policy": "hybrid",
  "salary_period": "year",
  "workplace_type": "hybrid",
  "salary_currency": "USD"
}
Extensions
{}
Native Structured
{
  "lists": [
    {
      "text": "In this role, you will: ",
      "content": "\n<li>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.</li>\n<li>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.</li>\n<li>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.</li>\n<li>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</li>\n<li>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.</li>\n<li>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.</li>\n"
    },
    {
      "text": "Qualifications",
      "content": "\n<li>Bachelor's and/or Master’s-level engineering degree or equivalent technical background with 3-5 years of hands-on experience in Reliability Engineering.</li>\n<li>Detailed understanding of sensors, high-performance computers, and ECUs, including common failure modes and associated validation methodologies.</li>\n<li>Expertise in reliability data analysis, risk assessment, and development of component reliability targets aligned with functional safety and business objectives.</li>\n<li>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).</li>\n<li>Experience in failure mode assessment, accelerated reliability testing, advanced field reliability monitoring, and/or prognostics and health management concepts.</li>\n<li>Personable, with the ability to lead and influence cross-functional engineering teams toward world-class reliability and dependability.</li>\n"
    },
    {
      "text": "Bonus Qualifications",
      "content": "\n<li>Demonstrated knowledge in Python-based data analysis tools such as PySpark, Pandas, NumPy, and SciPy.</li>\n<li>ASQ Certified Reliability Engineer, or similar professional recognition</li>\n<li>An understanding of ISO 26262 Functional Safety</li>\n"
    }
  ],
  "country": "US",
  "createdAt": 1769457824471,
  "updatedAt": null,
  "categories": {
    "team": "Quality and Reliability",
    "level": "All Levels",
    "location": "Foster City, CA",
    "commitment": "Full-time",
    "department": "Supply Chain Quality and Reliability",
    "allLocations": [
      "Foster City, CA"
    ]
  },
  "salaryRange": {
    "max": 197000,
    "min": 164000,
    "currency": "USD",
    "interval": "per-year-salary"
  },
  "workplaceType": "hybrid"
}
Get this page with API

Rendered from the bluedoor Job Postings API. Reproduce it:

GET https://api.bluedoor.sh/job-postings/v1/jobs/aa1f710d2463f7389ded564ee14b6da33455381e?include=descriptionJSON
GET https://api.bluedoor.sh/job-postings/v1/orgs/518be277-8ec5-4735-b0ad-193a2bc397c7JSON
GET https://api.bluedoor.sh/job-postings/v1/sources/45f1a12e-419b-4b96-93be-f479c9356a1bJSON
GET https://api.bluedoor.sh/job-postings/v1/jobs/aa1f710d2463f7389ded564ee14b6da33455381e/eventsJSON