Overview
We are the movers of the world and the makers of the future. We get up every day, roll up our sleeves and build a better world together. At Ford, we're all a part of something bigger than ourselves. Are you ready to change the way the world moves?
Ford's Electric Vehicles, Digital and Design (EVDD) team is charged with delivering the company's vision of a fully electric transportation future. EVDD is customer-obsessed, entrepreneurial, and data-driven and is dedicated to delivering industry-leading customer experience for electric vehicle buyers and owners. You'll join an agile team of doers pioneering our EV future by working collaboratively, staying focused on only what matters, and delivering excellence day in and day out. Join us to make positive change by helping build a better world where every person is free to move and pursue their dreams.
In this position, you will work with multiple teams and help set reliability targets at the system and subsystem level. You will oversee the design validation test campaigns throughout different stages of vehicle development from proof of concept to the launch. You will be defining test plans, quantities and test profiles in collaboration with subject matter experts based on the physics of failure, complexity of systems, and technology readiness levels. You will be identifying failure modes and design test methods to exercise them. This role is expected to support an entire vehicle.
Responsibilities
- Define reliability targets for different systems and subsystems by cascading top level requirements based on system complexity and architecture maturity
- Develop design validation test campaigns for different systems in a vehicle at different stages of development from concept to launch
- Specify test resources and design accelerated test profiles for different systems and subsystems
- Lead efforts to analyze root causes of failures and interpret results from SEM, XRD, optical microscopy, and other tools used in forensic engineering
- Work in a cross-functional environment with individuals from different teams and backgrounds; you will be presented with problems from diverse disciplines of engineering
- Use connected vehicle platforms to inform hardware design by generating duty cycles based on real-life usage data
- Conduct DFMEA studies for different systems
Qualifications
B.S. in Mechanical, Electrical, or Chemical Engineering, Materials Science, Applied Physics or Chemistry with 5+ years of relevant reliability engineering, test design, and failure analysis experienceAdvanced knowledge of reliability engineering mathematics, including statistical distributions and confidence levels; fleet data analysis; failure vs suspension data treatmentAdvanced knowledge of accelerated life testing : test plan development, sample sizes, sequence ordering, duty cycle / mission profile developmentSolid understanding of physics of failure focusing on fatigue, wear, environmental degradation (temp cycling, UV, humidity, oxidation, vibration, etc.)Familiarity with industry standards for shock, vibration, corrosion, environmental exposure, etc.Ability to work with multiple teams from mechanical, electrical, chemical, and other engineering backgroundsDemonstrated track record of leading successful root cause analysis campaigns in a multi-functional environmentDemonstrated ability to balance depth and breadth to optimize deliverables in a fast-paced environmentEven better, you may have
M.S. or Ph.D. in Mechanical or Electrical EngineeringAutomotive background / experience is highly desired, but not necessarySpecific coursework focused on Reliability Engineering is highly desired but not requiredExperience with Microsoft Office, Confluence, and JiraExperience with instrumentation and measurement of powertrain systems in a lab environmentStrong written and verbal communication skillsSoftware skills for fleet analysis
Python or similar for data analysis (High importance) with 3+ yearsCloud computing for data processing, storage, automation : Google Cloud Platform (preferred) or AWS / Azure (Medium importance) with 1+ yearRelational databases / data warehouses and SQL for querying fleet connected vehicle data (High importance) with 2+ yearsData visualization tools like Power BI, Tableau, Looker Studio (Medium importance) with 1+ yearYou may not check every box, or your experience may look a little different from what we've outlined, but if you think you can bring value to Ford Motor Company, we encourage you to apply!
Benefits and additional information
This position is a salary grade 8.For more information on salary and benefits, click here : https : / / fordcareers.co / GSRSP4Visa sponsorship is available for this position. Candidates must be legally authorized to work in the United States.We are an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, religion, color, age, sex, national origin, sexual orientation, gender identity, disability status or protected veteran status. In the United States, if you need a reasonable accommodation for the online application process due to a disability, please call 1-888-336-0660.Onsite work of up to three days per week may be required for candidates within commuting distance of a Ford hub location.
LI-Hybrid #LI-JD2
Responsibilities
What you'll do : Define reliability targets for different systems and subsystems by cascading top level requirements based on system complexity and architecture maturityDevelop design validation test campaign for different systems in a vehicle at different stages of development from concept to launchSpecify test resources and design accelerated test profiles for different systems and subsystemsLead efforts to analyze root causes of failures and interpret the results of SEM, XRD, optical microscopy, and other tools used in forensic engineeringWork in a cross-functional environment with individuals from different teams and backgrounds; you will be presented with problems from diverse disciplines of engineeringUse connected vehicle platforms to inform hardware design by generating duty cycles based on real-life usage dataConduct DFMEA studies for different systemsJ-18808-Ljbffr
