Engineering Lead - Coremesh Ontology and Knowledge Graph

You'll have...

• Bachelor's degree in Computer Science, Information Science, Engineering, or a related field, or equivalent experience.

• 7+ years in ontology engineering, knowledge graphs, semantic modeling, or master data, including technical leadership.

• Strong data and software engineering skills, including APIs and systems integration.

• Experience turning complex domain knowledge into maintainable models.

• Familiarity with metadata, lineage, entity resolution, and data quality practices.

Even better, you may have...

• Manufacturing, industrial, or other complex operational domain experience.

• OWL/RDF, property graphs, GraphQL, or data contract standards.

• Semantic services that support AI retrieval or agent applications.

• Google Cloud Platform (BigQuery, AlloyDB/PostgreSQL).

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
• 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
• Generous vacation time, sick/personal time, and paid holidays, including between Christmas Eve and New Year’s Day

 

This position is leadership level 6 and ranges from $115,500-$218,100. 
 

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/LL6

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 with a requirement to be onsite four or more days per week. 

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What you'll do...

Model Manufacturing

• Work with plant experts to define canonical concepts, relationships, identifiers, and terminology.

• Map source systems into the ontology and resolve records from different systems into one entity.

• Set versioning, ownership, provenance, validation, and change control for ontology assets.

Serve It to Agents and Apps

• Provide interfaces for retrieval, agent workflows, and applications, including InZone, the mobile app supervisors use to run a shift, which puts production status, issues, parts, and team chat in one place.

• Build quality checks for ambiguity, duplicates, gaps, and the impact of changes.

• Explain modeling decisions so consuming teams use the services correctly.

Lead the Work

• Guide the engineers and data scientists who extend the ontology.

• Partner with the teams that build on the ontology, including ATP's AI agents for production issues and its in-house model of factory operations.