Join Ford’s mission to modernize automotive manufacturing through innovative data science, intelligent data pipelines, and AI/ML solutions. As a Data Anchor and AI/ML Engineer, you will be at the intersection of the digital and physical—architecting and deploying cutting-edge machine learning models and robust data ecosystems that bring predictive analytics, automation, and intelligence to the factory floor. You will help build the data platforms that power our plants, enabling real-time insights, optimized vehicle scheduling, and resilient operations that scale with the future of mobility.

This is a great opportunity to drive the delivery of key enterprise objectives in building Ford’s flagship products. In this role, you will act as a technical anchor, working alongside a unique blend of software engineers, DevOps, automation, controls, and manufacturing business personnel. You will be responsible for ideating, building, and scaling billion-dollar data-driven ideas—leveraging streaming IoT telemetry, massive data lakes, and cutting-edge Generative AI—for the manufacturing of iconic Ford products. This is a rare opportunity to put your signature on how Ford uses data and AI to manufacture vehicles.

AI/ML & Generative AI: Architecting, developing, and deploying data leveraged through LLM models and toolsets such as Gemini Enterprise to build advanced generative AI solutions.
Data Engineering & IIoT Pipelines: Designing factory data standards streamed through Kafka and MQTT for IoT telemetry.
Data Anchoring & Strategy: Acting as the technical lead for data initiatives, defining data architecture standards, mentoring team members, and ensuring alignment with enterprise data strategies across hybrid environments.
Cloud & Big Data Infrastructure: Designing and maintaining robust data architectures with traditional SQL, BigQuery for enterprise data warehousing, MongoDB for flexible NoSQL document storage, and Hadoop ecosystems for distributed big data processing.
Data Modernization: Leading the migration and integration path from legacy on-premise systems (including legacy Hadoop clusters) to modern, cloud-native data platforms on GCP.
Domain Expertise: Gaining a deep understanding of the core functionality of Industrial Systems to drive data-driven optimizations and predictive modeling.
Model & Data Monitoring: Identifying and implementing monitoring solutions for data drift, model performance, and pipeline health using tools like Dynatrace, Splunk, and native cloud monitoring.

Education: Master’s degree in Data Science, Computer Science, Computer Engineering, Statistics, or a related highly quantitative field.
Experience: 5+ years of combined experience in Data Science, Data Engineering, and deploying AI/ML models into production environments.
Technical Skills:
- Strong proficiency in programming languages for data and ML, specifically Python and SQL.
- Deep expertise in big data processing frameworks (e.g., Hadoop, Apache Spark, Kafka).
- Hands-on experience with streaming data and Industrial IoT protocols, specifically MQTT.
- Advanced database experience across relational and non-relational systems, including deep knowledge of BigQuery.
- Expertise in cloud platforms (GCP preferred) and leveraging advanced AI services like Gemini Enterprise and Vertex AI.
- Exposure to machine learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn) and predictive modeling techniques.
- Experience exposing ML models via RESTful APIs or microservices.
Soft Skills:
- Proven ability to act as a "Data Anchor," guiding technical architecture and mentoring junior data scientists/engineers.
- Excellent communication, interpersonal, and presentation skills, with the ability to translate complex concepts to non-technical business stakeholders.
- Comfortable interacting with global plant IT and business customers to clarify needs and define data requirements.
- A quick learner, adaptable to changing environments, and highly effective within a diverse global team.

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.

For a detailed look at our benefits, click here: https://fordcareers.co/GSR

This position ranges from salary grade 6-8 and ranges from $85,400-$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.

Visa sponsorship is NOT 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.

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Data Anchor

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