AI/Machine Learning & Data Analytics Developer at Ford Global Career Site

Dearborn, Michigan, United States -

Full Time

Start Date

Immediate

Expiry Date

19 Jan, 26

Salary

0.0

Posted On

21 Oct, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Reporting, Data Visualization, MLOps, Cloud Environments, Python, JavaScript, React, Node.js, SQL, NoSQL, API Design, Agile Methodologies, Machine Learning, Data Pipelines, Front-End Development, Big Data Tools

Industry

Motor Vehicle Manufacturing

Description

Lead the development, testing, and deployment of comprehensive data reporting and visualization dashboards for critical engineering and business environments (e.g., Requirements & DV, CDP/CDR, FMA, CAD/BOM Alignment). Partner with stakeholders (e.g., Vehicle Signoff Admins, Process Owners) to define metrics and create display solutions for global and regional use-cases. Design and implement robust, scalable data pipelines and MLOps frameworks in cloud environments (GCP, AWS) to ensure efficient deployment and maintenance of analytical and AI/ML solutions. Develop data connection points and integration strategies to enhance data reintegration across disciplines like Design Verification and FMA. Architect, develop, and deploy advanced AI/ML solutions, including Generative AI applications, to solve complex engineering and operational challenges. Translate vehicle engineering and broader business problems into appropriate mathematical representations and AI/ML solutions (classification, prediction, intelligent automation). Develop intuitive front-end user interfaces for seamless interaction with analytical systems and actionable insights. Root cause data report and dashboard errors, collaborating with users and IT to implement sustainable solutions. Work with IT product teams to identify data model needs, extraction protocols, and report formats. Ensure data and solution quality and integrity throughout the development lifecycle. Operate within an Agile framework, authoring user stories and prioritizing backlog items. Develop training documentation and learning materials for new analytics and AI solutions. Collaborate effectively across the business to navigate IT and business constraints, ensuring practical and scalable solutions. Established and active employee resource groups Bachelor's degree in Computer Science, Engineering, Data Science, Statistics, or a related quantitative field. 3+ years of experience in data reporting, modeling, visualization, and advanced analytics. 2+ years of experience developing production full-stack applications (e.g., Python, JavaScript/TypeScript, React, Node.js). 1+ year experience designing and implementing data pipelines and MLOps in cloud environments (GCP, AWS, Azure). Proficiency in automated reporting tools (e.g., Alteryx, QlikView, Tableau, Power BI). Working knowledge of database systems (SQL, NoSQL) and API design (REST/GraphQL). Familiarity with cloud-based AI tools (e.g., Vertex AI, SageMaker). Strong analytical, problem-solving, and communication skills, translating complex problems into data-driven solutions. Ability to collaborate effectively with technical and business stakeholders in ambiguous environments. Master's degree in relevant quantitative disciplines (e.g., Computer Science, Data Science, AI, Engineering). 5+ years of Python development experience, including advanced data manipulation (Pandas) and ML model development (NLP, PyTorch, TensorFlow). 3+ years developing and deploying solutions on major cloud platforms (GCP, AWS). 3+ years of Front-End Development experience (React, JavaScript, HTML) for analytical applications. Experience with PLM systems (e.g., Siemens Teamcenter PLM / Active Workspace). Familiarity with Ford Automotive Procedures for Design Verification and Non-Conformance. Working experience with Agile methodologies and tools (e.g., Jira). Experience with big data tools (e.g., Hadoop, Spark). Global collaboration experience. Demonstrated ability to evaluate, champion, and integrate new technologies, articulating business value.

Responsibilities

Lead the development and deployment of data reporting and visualization dashboards while collaborating with stakeholders to define metrics. Design and implement data pipelines and MLOps frameworks in cloud environments to support AI/ML solutions.