Anduril Industries
Reliability Engineer
About this role
Anduril Industries seeks a Reliability Engineer to ensure autonomous defense systems perform reliably across their entire lifecycle. You'll conduct predictive analysis, lead failure investigations, and drive design improvements through cross-functional collaboration with engineering, manufacturing, and operations teams.
What you'll do
- Conduct Failure Modes & Effects Analysis (FMEA) and Fault Tree Analysis (FTA) to identify design risks
- Perform predictive reliability analysis using industry standards to calculate system performance metrics
- Develop and execute qualification and validation test plans including environmental and accelerated testing
- Lead root-cause investigations on field failures and drive corrective actions to closure
- Partner with manufacturing and quality teams to optimize assembly processes and production readiness
- Develop maintainability models and preventative maintenance plans using statistical methods
What they're looking for
- Reliability engineering and failure analysis
- FMEA and Fault Tree Analysis
- Predictive reliability analysis and Weibull analysis
- Test plan development and execution
- MIL-HDBK-217 and MIL-HDBK-472 standards
- Root-cause analysis and CAPA processes
- Cross-functional collaboration and communication
- Hardware design and production processes
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Anduril Industries
Anduril Industries builds autonomous defense systems including underwater vehicles, unmanned aircraft, and electronic warfare platforms for the Department of Defense. The company is hiring across mechanical engineering, mission operations, software development, technical leadership, and advanced manufacturing roles to support the design, deployment, and production of these mission-critical systems.
- Website
- anduril.com
Likely interview questions
- Walk us through your experience leading an FMEA or FTA effort. How did you drive cross-functional alignment to implement design improvements, and what was the outcome?
- Describe a time you performed predictive reliability analysis or Weibull analysis on a fielded product. What data sources did you use, and how did the results influence design or maintenance decisions?