Overview
On Site
USD 104,000.00 - 222,000.00 per year
Full Time
Skills
Energy
Development testing
Manufacturing
FMEA
Modeling
Product design
ROOT
Product development
Research
Continuous improvement
Science
Materials science
Electrical engineering
Reliability engineering
Testing
Physics
Statistics
Distribution
Estimating
Monte Carlo method
Failure analysis
Microscopy
Scanning electron microscope
SEM
EDX
Design
Computer Aided Design (CAD)
Data
3D computer graphics
Finite Element Analysis
Programming languages
Python
Mechanical engineering
PPO
Payroll
Health care
FSA
Finance
Apache Flex
Legal
Insurance
Job Details
As a Staff Reliability Engineer focusing on Tesla Energy Systems, you will play a key role in designing reliability into Tesla's industrial and residential products. This role follows the reliability lifecycle of the product from concept to design, development testing/analysis, manufacturing, and field operation to design-in, confirm, and grow exceptional reliability at every stage. You will investigate failures through physics of failure analysis and physical testing to accurately predict the charging system's robustness and optimize product reliability while accelerating Tesla's next gen products' time to market.
Responsibilities
Requirements
Compensation and Benefits
Benefits
Along with competitive pay, as a full-time Tesla employee, you are eligible for the following benefits at day 1 of hire:
Responsibilities
- 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
Requirements
- 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
Compensation and Benefits
Benefits
Along with competitive pay, as a full-time Tesla employee, you are eligible for the following benefits at day 1 of hire:
- Aetna PPO and HSA plans > 2 medical plan options with $0 payroll deduction
- Family-building, fertility, adoption and surrogacy benefits
- Dental (including orthodontic coverage) and vision plans, both have options with a $0 paycheck contribution
- Company Paid (Health Savings Account) HSA Contribution when enrolled in the High Deductible Aetna medical plan with HSA
- Healthcare and Dependent Care Flexible Spending Accounts (FSA)
- LGBTQ+ care concierge services
- 401(k) with employer match, Employee Stock Purchase Plans, and other financial benefits
- Company paid Basic Life, AD&D, short-term and long-term disability insurance
- Employee Assistance Program
- Sick and Vacation time (Flex time for salary positions), and Paid Holidays
- Back-up childcare and parenting support resources
- Voluntary benefits to include: critical illness, hospital indemnity, accident insurance, theft & legal services, and pet insurance
- Weight Loss and Tobacco Cessation Programs
- Tesla Babies program
- Commuter benefits
- Employee discounts and perks program
- Expected Compensation
$104,000 - $222,000/annual salary + cash and stock awards + benefits
Pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. The total compensation package for this position may also include other elements dependent on the position offered. Details of participation in these benefit plans will be provided if an employee receives an offer of employment.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.