In this position... 

At Ford Motor Company, we believe freedom of movement drives human progress. We also believe in providing you with the freedom to define and realize your dreams. With our incredible plans for the future of mobility, we have an exciting opportunity for you to join our expanding area of Prognostics.

Are you passionate about leveraging modern day methodologies/tools to understand automotive systems, study and predict the degradation or occurrence of a problem in a vehicle component/system?  Would you love to accelerate our efforts to build amazing experiences and software products in the Connected Vehicles space - with data? 

 We are seeking top-tier Systems Engineering professionals who are data driven, self-motivated and detail oriented to help develop and deliver breakthrough Prognostic Features.

You'll have...

Master’s degree in Computer Science, Automotive Engineering, Systems Engineering, Mechanical Engineering, Electrical Engineering, Mechatronics Engineering, or a related field.   1+ years of programming experience using SQL, JAVA, C, C++ or Python along with MATLAB/Simulink, SysML, or similar. 2+ years of experience performing systems analysis and designing systems, subsystems, or components defining requirements as described above.  2+ years of leveraging data-driven analytics tools to analyze Connected Vehicle Data or large data sets 2+ years of experience: investigating and resolving feature-specific issues during product development and launch; or analyzing system failure points and evaluating solution proposals including conducting high level FMAs and FMEAs.    2+ years of experience: interfacing cloud-to-vehicle modem communications; or applying network communication protocols, transport protocols, and payload optimization techniques.  2+ years utilizing automotive communication protocols (CAN, LIN, Ethernet, etc.)

Even better, you may have…

5+ years of proven knowledge of Robust Engineering Fundamentals including P-Diagrams, Noise Factors.  Knowledge of vehicle distributed systems, components, vehicle architecture, sensors, and signal processing.  Experience with Model-Based Systems Engineering (MBSE) methodologies.  Experience working with Atlassian JIRA, JAMA, GitHub and Team Center applications (VSEM, etc.)  Ability to clearly communicate technical ideas/findings to cross-functional engineering teams. 

You 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!

 

As an established global company, we offer the benefit of choice. You can choose what your Ford future will look like: will your story span the globe, or keep you close to home? Will your career be a deep dive into what you love, or a series of new teams and new skills? Will you be a leader, a changemaker, a technical expert, a culture builder…or all of the above? No matter what you choose, we offer a work life that works for you, including:
• Immediate medical, dental, vision and prescription drug coverage
• Flexible family care days, paid parental leave, new parent ramp-up programs, subsidized back-up child care and more
• Family building benefits including adoption and surrogacy expense reimbursement, fertility treatments, and more
• Vehicle discount program for employees and family members and management leases
• Tuition assistance
• Established and active employee resource groups
• Paid time off for individual and team community service
• A generous schedule of paid holidays, including the week between Christmas and New Year’s Day
• Paid time off and the option to purchase additional vacation time.

For a detailed look at our benefits, click here:

https://fordcareers.co/GSR-HTHD 

This position is a range of salary grades 6-8 .

Visa sponsorship is available for this position.
Candidates for positions with Ford Motor Company must be legally authorized to work in the United States. Verification of employment eligibility will be required at the time of hire.

We are an Equal Opportunity Employer committed to a culturally diverse workforce. 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.

#LI-Hybrid  

 

What you'll do...

Lead the development of new Prognostics features at the systems engineering level from concept feature development to production. This includes defining requirements, designing architecture, implementing code, and conducting thorough testing. Collaborate with cross-functional teams to gather business requirements, translate them into tangible technical specifications, and drive feature development. This involves working closely with software engineers, data scientists, hardware engineers, and product managers. Evaluate potential design options to make appropriate proposals considering feature requirements, available technology, efficiency, and platform capabilities. This includes conducting feasibility studies, prototyping solutions, and analyzing performance metrics. Automate testing procedures and build comprehensive test suites to ensure the quality and reliability of Prognostic features. This includes designing test cases, developing automated test scripts, and analyzing test results to identify and resolve issues. Develop and author product-specific requirements, evaluating quality and aiding to triage issues to determine root cause. This involves working with development teams to ensure that the code meets the required specifications and to resolve any defects. Monitor Key Performance Indicators (KPI) dashboards, tracking metrics and providing critical feedback around customer experience. This includes identifying areas for improvement, proposing solutions, and working with the team to implement those solutions. Model the system from the data abstraction layer, simplifying complex systems by breaking them down into smaller, more manageable parts. This involves using modeling tools and techniques to represent the system's behavior and to facilitate communication and collaboration among team members.