Field Reliability Engineer

• As a Field Reliability Engineer, you will apply reliability engineering concepts to continuously improve reliability for vehicle systems across Zoox’s two autonomous vehicle fleets.
• Utilize reliability statistics to identify reliability trends in the field and provide a clear description of emerging risks.
• Facilitate root cause investigations, with a major focus on physics of failure and using a data-driven approach.
• Apply statistical analysis of reliability data by identifying the most appropriate life metric to create meaningful reliability analyses, ranging from simple time, miles analysis or cycles of operation to big data physics of failure-driven approaches. Utilize big data for reliability, exploiting the new possibilities that a connected vehicle and fleet service management allow.
• Create reliability forecasts to provide visibility to design, service, manufacturing, quality, and supply chain allowing early understanding of field issues and a coordinated technical and business strategy for deployment of containment and countermeasures.
• Drive root cause investigations for field failures in partnership with design engineering, service, and quality, with a major focus on physics of failure and using a data-driven approach.
• Analyze usage, stress and environmental conditions from the vehicle fleets to validate and continuously improve product requirements and test methods.
• Provide reliability design insights and process guidelines based on field findings and maintain a knowledge base of reliability lessons learned to enable continuous improvement.

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• Minimum requirement is a Bachelor of Science in an engineering discipline or equivalent with two or more years of industry experience in a reliability engineering role. Level of role depends on experience and qualifications. In addition, a strong technical background and interest in reliability.
• Working knowledge of applied statistics in field of Reliability
• Domain knowledge and hands-on experience with mechanical or electrical systems
• Practical hands-on experience in the failure analysis process

Bonus Qualifications

• A deep understanding of reliability concepts, and proven expertise in applying advanced reliability data analysis methods to drive priorities in reliability
• Application of fault tree and block diagram analyses to assess system reliability
• Experience with statistical software for reliability such as JMP, ReliaSoft suite, or R
• Understanding of fleet reliability monitoring metrics and reliability KPIs
• Experience in Python or R, creating reliability data visualizations
• Knowledge of database structures and practical understanding and use of SQL. Experience in working with large data sets.
• Familiarity with failure analysis techniques such as optical microscopy, X-ray, CT, FTIR, SEM, EDS. Working knowledge of vehicle dynamics, electromechanical system design, and metallic and plastic part design and manufacturing processes
• ASQ Certified Reliability Engineer or similar professional certification

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