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At Ford, you’ll work on ideas that matter, alongside passionate people who want to make a global impact. Together, we’re shaping the next era of transportation—grounded in purpose, driven by progress. Make your move.
We made history and now we work to transform the future – for our customers, our communities and our families. You'll see your work on the road every day, helping people move freely and pursue their dreams. At Ford, you can build more than vehicles. Come build what matters.
In this position...
You will join the team driving Ford’s Enhanced Central Gateway (ECG) and Telematics Control Unit (TCU), critical components of the Fully Networked Vehicle (FNVx) architecture. This role offers the opportunity to own the full lifecycle of issue resolution, from initial discovery in prototypes to final implementation in the field. You will collaborate closely with in-house software development teams to improve early issue detection methods and enhance feature performance for global vehicle programs. You will also leverage advanced machine learning, artificial intelligence, and big data pipelines to proactively identify anomalies, create predictive models, and deploy data-driven solutions that uplift vehicle quality and customer satisfaction.
What you'll do...
Advanced Analytics & AI:
Craft effective inputs and utilize prompt engineering to guide AI models in producing accurate and relevant diagnostic outputs.
Manage, query, and wrangle large datasets using SQL, transforming raw data into insightful visualizations to drive smart decision-making.
Design, train, and deploy machine learning and deep learning models, supervised and unsupervised, to production using end-to-end MLOps pipelines.
Triage:
Lead active triage of ECG and TCU issues raised by global test teams, vehicle programs, and Ford dealerships during pre-production prototype milestones through post-production milestones.
Drive the daily triage of global technical issues using JIRA to prioritize and route defects, while leveraging GitHub to reference source code and aid in deeper root cause analysis.
Troubleshoot complex, interconnected systems comprised of both physical and software-based systems.
Support cross-functional issue analysis, identifying permanent solutions at a vehicle system level.
Improve internal systems and methods for remote software error detection related to ECG and TCU.
Quality:
Act as the first technical contact for ECG and TCU issues in customer vehicles as identified by Ford’s global dealership network.
Work with cross-functional teams to quickly identify faulting systems, subsystems, or modules to enable dealership repairs for customers.
Support large scale data analysis across entire fleets of customer fleets with the goal of identifying patterns of behavior with limited information.
General:
Apply an abundance of curiosity for vehicle architectures to proactively investigate technical anomalies.
Apply critical thinking and strong problem-solving skills to analyze complex problems and produce innovative solutions.
Demonstrate exemplary communication skills, building an environment of clear and effective collaboration within the immediate team and in-house software development teams.
Analyze connected vehicle data communicating with Ford’s diagnostic backend to validate system health.
You'll have...
BS in Electrical, Computer, or Software Engineering or related technical field.
Proficiency in programming languages including Python, R, and SQL.
Strong foundation in mathematics and statistics, including linear algebra, calculus, and probability.
Working knowledge of modern data platforms (e.g., BigQuery) and cloud computing environments (GCP, Azure, or AWS).
Proficiency in data visualization tools and libraries (e.g., Power BI, Looker Studio, Matplotlib).
Experience with Large Language Model (LLM) ecosystems and tools.
Experience building and managing MLOps pipelines (e.g., MLflow, Kubeflow, model registries, feature stores, CI/CD)
Basic proficiency in issue management platforms (Jira)
Even better, you may have...
MS in Electrical, Computer, or Software Engineering or related technical field.
Familiarity with version control systems (e.g., Git/GitHub) and software development lifecycles.
Hands-on experience with popular machine learning and deep learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn, or XGBoost).
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:
This position is a salary grade 7 and ranges from $97,140-162,540.
Final determination of salary grade will be based on candidate's skills and experience, and base salary will be set within the applicable range according to job scope, responsibility and competitive market value.
For more information on salary and benefits, click here: https://fordcareers.co/GSR
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. 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.
This position is hybrid. Candidates who are in commuting distance to a Ford hub location may be required to be onsite four or more days per week. #LI-Hybrid
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