AI/ML Engineer

As an AI/ML software engineer in the Supply Chain IT space, you will be the driving force for delivering Ford’s "AI-First" supply chain transformation. This role is focused on the applied implementation of AI. You will develop and deliver the integration of high-performance models to solve complex supply chain problems. Central to this role is the adoption of an AI-Driven Software Development Life Cycle (SDLC) leveraging agentic workflows, AI-assisted coding, and automated testing to deliver robust solutions at industrial speed. You will bridge the gap between abstract business problems and scalable technical execution. This role demands a blend of technical expertise in AI/ML, advanced analytics and data platform engineering, functional expertise in supply chain, and strong technical leadership to influence stakeholders and deliver transformative results. You will focus on establishing and standardizing the AI-based SDLC. You aren’t just building chatbots. You are building intelligent global supply chain solutions, helping the business manage risk, build resilience, and keep our factories running.

Minimum Qualifications

Bachelor's degree in computer science, Information technology, Data Science, or related technical field. A Master’s degree is good to have

5+ years of software engineering experience.

3+ years of progressive experience in AI/ML, data science, or advanced analytics, with a proven track record of delivering production-grade solutions in large enterprise environments.

Strong proficiency in Python and SQL. Familiarity with Graph Query Languages (e.g., Cypher) is good to have.

Demonstrated experience with MLOps principles and tools (e.g., GCP AI Platform, Kubeflow, MLflow) and designing / implementing AI-specific SDLCs.

Demonstrated experience in Infrastructure as Code (IaC) & CI/CD. Proficiency with Terraform for managing cloud infrastructure, alongside modern CI/CD tools such as Tekton, Jenkins, or GitHub Actions.  

Experience in LLMOps capability: Experience designing, deploying, and maintaining LLM-powered applications in production, with focus on prompt engineering, RAG pipelines, safety controls, hallucination mitigation, observability, cost optimization, and continuous testing and evaluation using metrics like accuracy,F1,BLEU, ROUGE etc and frameworks like RAGAS , DeepEval etc  

Strong technical expertise in cloud services (GCP/Vertex AI) and data integration patterns

Strong analytical, problem-solving, and critical thinking skills.

Exceptional communication & interpersonal skills, to translate complex AI logic into strategic recommendations for supply chain business leaders.

Programming and tools requirements:

Must have 3+ years of experience in Python, FastAPI / Flask , REST APIs, SQL / NoSQL database, API authentication and authorization, Agent development and orchestration, Google ADK,  Model Context Protocol , Prompt engineering and context management  

Must have 1-2 years of experience in CI/CD pipelines, Tekton , Git / GitHub  

Knowledge of RAG pipelines, Embeddings and vector search, LangChain / LangGraph, Kubernetes, Docker, Grafana or Dynatrace is desired by not a must have

Preferred Qualifications

AI-SDLC Experience: Proven track record of using AI tools to enhance personal or team productivity (e.g., Agentic workflows, RAG-based requirement synthesis).

Requirement Engineering: Experience in a product engineering role with a proven track record of translating business needs into technical specifications for applied AI implementation.

Knowledge Graph: Understanding semantic ontologies and how they enable advanced analytics.

Supply Chain Domain Knowledge: Functional understanding of supply chain operations, including demand & capacity planning, logistics, sustainability & risk management, resilience, etc.

Research to Production: Ability to research and rapidly apply & build a functional prototype that meets Ford’s standards for security and scalability.

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.

This position is a salary grade 7-8 and ranges from $99,600-$192,900.    
 

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

#LI-GR1 

Business Requirement Gathering: Partner with supply chain functional leads to elicit and document business requirements and translate them into technical specifications for AI-driven decision support tools, ensuring every solution delivers measurable business value. 

Model Integration & Deployment: Act as the lead software engineer for applied AI implementation. Take pre-developed models provisioned by the organization and successfully deploy them within the supply chain GCP space. 

Front-end development: Develop smart visuals to highlight KPI and metrics using Angular, TypeScript, HTML, CSS/SCSS, RxJS, NgRx, Angular Material or similar component libraries 

AI-Driven SDLC Execution: Champion and implement AI-assisted development practices. Implement agentic workflows (e.g., AutoGen, CrewAI) and Use LLM-based tools (e.g., GitHub Copilot, automated PR agents, and AI-generated documentation) to accelerate delivery with high code quality for the Supply Chain Analytics platform. 

Technical Standardization: Develop reusable integration patterns and data contracts to ensure that AI solutions can be scaled across multiple business units without redundant engineering effort. 

Collaboration: Participate in architecture reviews, technical design discussions, code reviews, and production readiness assessments. Collaborate with SCM analytics team members and business partners to develop effective analytics solutions, participate in UAT, defect resolution, and deployment activities. 

Learning and development: You will be focused on continuous learning, research on relevant new tech stacks, industry trends and available tools in the organization. Attend training, develop POCs and pave the way for other team members. 

Modernize: Review current reporting solutions and use cases. Ideate and convert them into AI based analytics solution