Data Scientist at Ford Motor Company

Dearborn, Michigan, United States -

Full Time

Start Date

Immediate

Expiry Date

07 Aug, 26

Salary

166200.0

Posted On

09 May, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Artificial Intelligence, Generative AI, Full-stack Development, MLOps, Google Cloud Platform, Amazon Web Services, Python, React, LangChain, LangGraph, Vertex AI, SQL, NoSQL, Docker, Kubernetes

Industry

Motor Vehicle Manufacturing

Description

We are looking for a Data Scientist with exceptional skills in Machine Learning (ML) and Artificial Intelligence (AI). We are seeking an experienced data scientist with a strong focus on building and maintaining sophisticated full-stack applications. The successful candidate will possess a proven track record of designing, developing, and deploying successful innovative Generative AI (GenAI) software solutions. This role requires a proven communicator who effectively interfaces between technical and business teams, translating complex AI capabilities and technical insights into actionable business value. What you'll do... Architect, develop, and deploy end-to-end agentic full-stack Generative AI (GenAI) applications that solve complex real-world problems, with a specific focus on improving engineering challenges and inefficiencies. Design and implement robust, scalable data science and Machine Learning Operations (MLOps) pipelines primarily within cloud environments like Google Cloud Platform (GCP) and Amazon Web Services (AWS), ensuring efficient deployment and maintenance of AI solutions. Lead the integration of new cloud technologies and AI tools (e.g., Vertex AI) into our workflows, continuously evaluating their potential and articulating their business value to drive innovation and efficiency. Develop intuitive and responsive front-end user interfaces that enable seamless interaction with agentic AI systems and effectively translate complex outputs into actionable insights. Acquire a deep understanding of vehicle engineering problems, translating them into appropriate mathematical representations and AI/ML solutions (classification, prediction, intelligent automation). Ensure the overall quality and integrity of data and solutions throughout the development lifecycle, from data collection and cleaning to model deployment You'll have... Bachelor's degree in Computer Science & Engineering, related field or equivalent combination of relevant education and experience 3+ years of experience building full-stack applications in production environments, with proficiency in Data Science, JavaScript/TypeScript, React, HTML and backend frameworks including Next.js, Node.js, Python, or Go 2+ year experience with database systems (SQL, NoSQL), API design (REST/GraphQL) and building scalable API services using frameworks such as Flask or FastAPI 2+ year experience deploying and maintaining applications in cloud-native environments (e.g., AWS, Azure, GCP) 2+ years of hands-on experience designing and building agentic workflows using modern AI frameworks and platforms, specifically LangChain, LangGraph, Google Agent Development Kit (ADK), and Google Vertex AI Experience with Context Engineering and utilizing the Model Context Protocol (MCP) to securely and seamlessly connect AI models with enterprise data sources, APIs, and development environments Experience implementing AI Evaluation frameworks (e.g., RAGEval) to systematically measure, benchmark, and ensure the quality, safety, and relevance of LLM outputs in production 2+ year experience working with DevOps tools (Docker, Kubernetes, Terraform, etc.) Leveraging and integrating GCP cloud-based AI tools like Vertex AI into production systems A strong passion for evaluating, championing, and integrating new technologies and tools, particularly within GCP, into existing workflows, with the ability to clearly articulate and justify their business value and impact Exceptional collaboration skills, with the ability to effectively interface between technical development teams and business stakeholders, understanding and navigating both IT and business constraints Comfortable working in ambiguous environments where problems are not always well-defined, and solutions require innovative thinking Even better, you may have... Master's degree in Computer Science & Engineering, related field or equivalent combination of relevant education and experience 5+ years of Python development experience, specifically for: Advanced data manipulation and analysis using libraries such as Pandas. 3+ years of experience in Machine Learning model development, including Natural Language Processing (NLP), utilizing deep learning frameworks (PyTorch, TensorFlow, Keras), and leveraging open-source model ecosystems like Hugging Face 3+ years of hands-on experience developing and deploying solutions on major cloud platforms, including Google Cloud Platform (GCP) or Amazon Web Services (AWS). Advanced experience with LLMOps, MLOps, and AIOps, including managing the end-to-end lifecycle, continuous evaluation, fine-tuning, and monitoring of Large Language Models in enterprise environments 3+ years of Front-End Development experience using modern web technologies like React, JavaScript, and HTML, to build intuitive user interfaces for AI applications. Experience with AIOps, MLops would be beneficial Domain experience in the automotive industry, specifically applying AI/ML to solve complex vehicle engineering challenges, connected vehicle data, autonomous systems, or manufacturing 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 range of salary grades 6-8 and ranges from $74,300-$166,200. 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 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. 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-MG3

Responsibilities

Architect and deploy end-to-end agentic full-stack Generative AI applications to solve engineering challenges. Design scalable MLOps pipelines and integrate cloud-based AI tools to drive business value.