Senior Reliability Engineer
TLDR
Data-driven reliability engineering role focusing on life data analysis, Weibull modeling, reliability testing, and cross-functional collaboration to improve product durability.
- Perform life data analysis using the Weibull distribution to evaluate product reliability and predict failure behavior.
- Analyze time-to-failure data from laboratory testing, accelerated life testing (ALT), HALT, HASS, and field returns to identify reliability trends and failure patterns.
- Develop reliability models, perform system-level reliability assessments, and apply reliability growth methodologies to track and improve product performance.
- Conduct reliability risk assessments using Failure Mode and Effects Analysis, DFMEA, and Fault Tree Analysis to identify potential failure modes and mitigation strategies.
- Lead root cause investigations and failure analysis for anomalies identified during testing or field performance.
- Clean, organize, and analyze reliability datasets, generate metrics (MTBF, MTTF, B10 life), and communicate insights to engineering teams and management.
- Collaborate with design, quality, and manufacturing teams to improve product reliability throughout the development lifecycle.
Qualifications:
- Typically requires a minimum of 5 years of related experience with a Bachelor’s degree; or 3 years and a Master’s degree; or a PhD without experience; or equivalent work experience.
- Strong knowledge of reliability engineering principles, life data analysis, and product failure mechanisms.
- Experience performing Weibull analysis and applying statistical distributions such as Weibull distribution, exponential, and lognormal.
- Experience with reliability risk assessment methods (FMEA, DFMEA, FTA) and executing reliability testing including ALT, HALT, and HASS.
- Strong statistical analysis and data interpretation skills with experience analyzing time-to-failure datasets and reliability metrics.
- Experience with reliability and statistical software tools such as ReliaSoft Weibull++, Ansys Sherlock, Minitab, and programming/analytical tools such as Python, R, or MATLAB.
- Strong analytical, problem-solving, organizational, and communication skills with the ability to present technical findings and reliability insights to cross-functional teams and management.
- Strong analytical and problem-solving skills with the ability to interpret complex reliability and statistical data.
- Detail-oriented and methodical, able to identify patterns, anomalies, and failure trends in datasets.
- Excellent technical communication skills, capable of presenting reliability findings, risks, and recommendations clearly to cross-functional teams.
- Collaborative mindset, working effectively with design, quality, manufacturing, and test engineering teams.
- Proactive and data-driven, able to identify potential reliability risks early in the product lifecycle and recommend mitigation strategies.
- Organized and able to manage multiple reliability assessments, testing activities, and projects simultaneously.
- Continuous learner, staying updated on emerging reliability engineering methods, statistical techniques, and analytical tools.
Benefits
Health Insurance
health, life, and disability insurance
401(k)
Paid Time Off
unbounded paid time off including parental leave
EVgo is a leading provider of fast charging solutions for electric vehicles, boasting over 1,100 charging stations across 40 states. We cater to the growing demand for convenient and reliable EV infrastructure by partnering with major businesses and automakers, driving forward the adoption of electric vehicles and enabling a seamless charging experience for all.