Lead AI Engineer

Job Description
We are the movers of the world and the makers of the future. We get up every day, roll up our sleeves and build a better world -- together. At Ford, we're all a part of something bigger than ourselves. Are you ready to change the way the world moves?
Do you believe data tells the real story? We do! Redefining mobility requires quality data, metrics and analytics, as well as insightful interpreters and analysts. That's where Global Data Insight & Analytics makes an impact. We advise leadership on business conditions, customer needs and the competitive landscape. With our support, key decision makers can act in meaningful, positive ways. Join us and use your data expertise and analytical skills to drive evidence-based, timely decision making.
As a Lead AI Engineer , you will serve as a technical anchor and mentor, leveraging your robust technical background and extensive experience in Data Science, MLOps, and AI/ML Engineering to guide the team in delivering cutting-edge analytical, machine learning, and generative AI solutions. You will be instrumental in shaping the technical direction, establishing best practices, and driving the successful execution of complex AI initiatives. The ideal candidate will possess strong business acumen, a deep understanding of data and AI technologies, and a proven ability to lead and influence technical teams to enhance key products within Global Data Insight & Analytics (GDI&A), focusing on improving customer experiences, driving revenue growth, and increasing operational efficiency.
You will lead technical efforts within a diverse team to develop innovative products for Sales and Services Data and Analytics (SSDA). Building healthy relationships and trust, and effectively collaborating with product managers, business stakeholders, and peers across Ford, is essential for guiding cross-functional alignment and technical excellence.
Responsibilities

• Technical Leadership & Mentorship: Provide technical guidance, mentorship, and code reviews to junior and senior AI engineers, fostering a culture of innovation, quality, and continuous learning.
• Architectural Design: Lead the design and architecture of advanced AI models, including Generative AI, machine learning (ML), and deep learning (DL) algorithms, to address complex business challenges at scale.
• Strategic Development: Drive the end-to-end development lifecycle of AI solutions, from conceptualization and data strategy to deployment and monitoring, ensuring alignment with strategic business objectives.
• Best Practices & Standards: Establish and enforce best practices for data preprocessing, feature engineering, model training, evaluation, and fine-tuning, ensuring optimal performance, reliability, and reproducibility across the team's projects.
• Scalable Solutions: Oversee the development and maintenance of robust, efficient, and scalable code using Python and relevant libraries (e.g., TensorFlow, PyTorch, scikit-learn), ensuring adherence to high software engineering standards.
• Documentation & Knowledge Sharing: Champion comprehensive documentation of architectural decisions, code, experiments, and results, facilitating knowledge sharing and onboarding within the team and across departments.
• Cross-functional Collaboration: Act as a primary technical liaison, collaborating effectively with product managers, business stakeholders, and cross-functional teams to translate complex business needs into technical requirements and deliver impactful AI solutions.
• Agile Leadership: Lead technical efforts within an agile development model, driving sprint planning, technical estimations, and ensuring timely delivery of high-quality AI products.
• Innovation & Research: Stay abreast of the latest advancements in AI/ML and Generative AI, evaluating new technologies and methodologies to continuously improve our capabilities and drive innovation.

Qualifications

• Minimum: Master's degree in Statistics, Computer Science, or a related quantitative field.
• Preferred: PhD in Statistics, Computer Science, or a related quantitative field.
• 7+ years of progressive experience in developing and building cloud-based applications and deploying machine learning models, with at least 2 years in a technical lead or anchor role .
• Deep theoretical understanding and practical application of advanced machine learning algorithms and techniques, including deep learning architectures and Generative AI models.
• Proven hands-on experience in leading the design, development, and implementation of AI/ML models using Python, with an emphasis on scalable and production-ready systems.
• Expertise with relevant libraries such as TensorFlow, PyTorch, and scikit-learn.
• Extensive experience with data preprocessing, advanced feature engineering, and rigorous model evaluation strategies.
• Exceptional problem-solving and analytical skills, with a demonstrated ability to lead complex technical initiatives and drive solutions independently and collaboratively.
• Outstanding communication, presentation, and documentation skills, with the ability to articulate complex technical concepts to both technical and non-technical audiences.
• Specific experience with leading projects on cloud computing platforms like AWS, Google Cloud, or Azure, including architectural design and resource optimization.
• Expert-level proficiency in Google Cloud Platform (GCP) services relevant to machine learning and generative AI, such as AI Platform, BigQuery, Dataflow, Vertex AI, and MLOps tools.
• Deep understanding and practical experience with a wide range of machine learning algorithms, techniques, and frameworks, including advanced deep learning, neural networks, transformer models, and ensemble methods.
• Proven track record in building, training, and deploying generative AI models and complex machine learning solutions using tools like TensorFlow, Keras, or PyTorch, with a focus on production readiness.
• Expertise with cloud-based data storage and processing technologies for efficient handling of large-scale datasets (experience with Tekton and Terraform for infrastructure as code is a strong plus).
• Ability to design, architect, and implement end-to-end machine learning pipelines for data ingestion, processing, modeling, deployment, and continuous monitoring, incorporating MLOps best practices.
• Exceptional proficiency in programming languages such as Python for data manipulation, analysis, model development, and API integration.
• Extensive experience with version control systems like GitHub, including leading code reviews and managing complex branching strategies.
• Strong understanding and practical experience with containerization technologies like Docker and orchestration platforms like Kubernetes for packaging and deploying machine learning models in production environments.
• Demonstrated leadership in problem-solving and analytical thinking, with the capacity to communicate complex technical concepts and influence technical direction effectively.
• Extensive experience with generative AI technologies and practices, including model fine-tuning, prompt engineering, and ethical considerations (is a significant plus).
• Strong foundation in software engineering practices and their application to AI engineering, including clean code, testing, and system design principles.
• Deep expertise in GCP and its comprehensive machine learning offerings, including strategic utilization for large-scale AI initiatives.
• Expert-level proficiency in open-source data science technologies such as Python, R, Spark, and SQL, and experience in integrating them into robust AI solutions.
• Strategic understanding and hands-on experience in designing and implementing MLOps methodologies, CI/CD pipelines for ML models, and model governance frameworks.
• Experience with real-time inference systems and low-latency model serving.
• Familiarity with data governance, data privacy, and ethical AI principles.

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 leadership level 6.
Salary and benefits vary by location;
For more information on salary and benefits outside of California , click here:
For more information on salary and benefits in California , click here:
This position is a range of salary grades 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 .
This position is hybrid (onsite four days per week) for candidates who are in commuting distance to a Ford hub location or remote for non-local candidates. #LI-Hybrid #LI-Remote DK01