Day to day activities:
General We run two sprints with typical agile ceremonies (stand-ups, planning, backlog grooming, demos, retrospectives) We use Jira, GitHub, JFrog, for tracking and publications. Quay and GCP for endpoints and apps. Often collaborate and build solutions with other agile teams across the data space, operations, software applications, and customer products (hardware/software/services) Typical day work with domain experts that want data or produce data from the vehicle and in the cloud (FordPass) to understand the meaning of this data transform the data meanings into a knowledge representation, model the data add this to our Knowledge Graph assist or lead ML tooling to help with this effort enable, assist, or lead the generation of artifacts using the Knowledge Graph guided by different customers identify and create better solutions, approaches, and methods demonstrate solutions by creating POCs, MVPs, and Production product integrationsYou'll have...
Bachelor’s degree in computer science, related field or a combination of education and equivalent experience. 8+ years of professional experience in software development. 3+ years of experience with graph databases, Resource Description Framework, SPARQL, Python. Fluent in design patterns, SOLID principles, declarative programming, data modeling, and TDD.Even better, you may have...
5+ years of experience in machine learning and knowledge graph integrations with lexicons or ontologies. 5+ years of professional experience with data modeling. 3+ years of experience in metadata analysis, information science, taxonomy, ontology, or lexicography. 3+ years of experience using machine learning capabilities to solve customer problems.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 childcare 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 GSR 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.
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What you'll do...
Ensure our ontologies provide comprehensive sub-domain coverage that are available for machine ingestion and inference. Deliver datasets, models, and knowledge that power ML components across the data ecosystem. Create software that decodes structed data into human and machine-readable entities. Create software that provides self-service, data discovery, and machine-driven recommendations. Integrate your solution into enterprise systems. Collaborate seamlessly with cross-functional teams. Iteratively develop and deliver proof of concepts, MVPs, and production releases.