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Tesla Staff Reliability Engineer Energy Products United States, California, Palo Alto 970733501
10.04.2025
What You’ll Do What You’ll Bring
- Set and communicate reliability requirements and targets for site, product, subsystem, and components
- Create Fault Trees and reliability block diagrams to assess system reliability and warranty analysis. Facilitate Design FMEA sessions to drive reliable design choices and improve validation test programs
- Analyze usage and environmental conditions from the field to improve requirement setting and testing methods
- Apply statistical analysis to test (accelerated life) and field (life) data to inform reliability physics modeling/analyses and associated corrective actions
- Work closely with Design and Reliability Data Engineers to create/interpret/validate numeric models of fielded and in-test products
- Specify reliability validation plans for components and subsystems using physics of failure. Provide guidance on sample size requirements and durations for reliability testing using lifetime models and reliability statistics
- Drive reliability assessments in product design reviews and clearly communicate risk at each phase of product development and for released products
- Facilitate failure analysis to understand root cause and drive resolution of failures occurring during product development. Research failure mechanisms to build more robust validation plans and influence design choices
- Influence supplier selection for higher reliability and provide clear guidance on reliability requirements and demonstration to suppliers
- Provide reliability design guidelines and apply reliability lessons learned to enable continuous improvement. Answer complex questions on fleet usage and behavior to enable proactive health monitoring, grow reliability, and minimize field failures
- Bachelor of Science in Materials Engineering, Mechanical Engineering, Electrical Engineering or related field and one or more years of industry experience in a reliability engineering role or equivalent experience
- Understanding of accelerated testing methods, governing equations, and physics of failure for different failure mechanisms
- Understanding of applied statistics and reliability statistics (Weibull distribution, Maximum Likelihood Estimation, Bayesian methods, Monte Carlo analysis, etc.)
- Working knowledge of failure analysis techniques such as optical microscopy, SEM, CSAM, X-ray, cross-sectioning and EDX
- Knowledge of the ReliaSoft Synthesis Platform, including Weibull++, BlockSim, ALTA, RGA, and xFMEA
- Knowledge of methods to design-in reliability, including electronic computer-aided design and mechanical computer-aided engineering (CAE) data into 3D finite element models (e.g. using Sherlock)
- Working knowledge of programming languages, preferably Python
- Knowledge of reliability growth techniques, such as Crow-AMSAA and Crow Extended is a plus
- Knowledge of reliability warranty analysis and reliability prediction methods
- Experience working with complex electronic and mechanical systems
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