Ford

Seeking an experienced Data Scientist to architect, develop, and deploy end-to-end agentic Generative AI full-stack applications for engineering challenges. This role involves designing MLOps pipelines, integrating cloud AI tools, developing front-end interfaces, and translating business needs into AI/ML solutions.

Full Stack Software Engineer focused on integrating AI, specifically LLMs, into applications. The role involves architecting systems with autonomous agents, utilizing a Model Context Protocol for live data interaction, and providing real-time streaming experiences. Key responsibilities include designing agentic loops, implementing tool-use capabilities, integrating with proprietary data silos, developing high-concurrency back-ends and streaming front-ends, optimizing RAG pipelines, and establishing AI evaluation and observability.

Applied AI/ML Engineer to lead Ford's AI-First supply chain transformation by integrating AI models into Enterprise Knowledge Graphs. The role focuses on applied implementation, agentic workflows, and an AI-Driven SDLC to solve complex supply chain problems, manage risk, and build resilience. Responsibilities include business requirement gathering, model integration, graph-based AI implementation, AI-Driven SDLC execution, pipeline/MLOps engineering, and technical standardization.

Data Engineer role focused on building and scaling end-to-end data and AI pipelines on GCP, integrating Gen AI capabilities like LLM-powered enrichment, RAG, and intelligent automation. Responsibilities include designing data models, implementing CI/CD, data governance, and mentoring junior talent, with a focus on powering AI/ML workloads and next-generation AI experiences.

This role focuses on developing and implementing AI capabilities to enhance engineering efficiency within Ford's suspension division. The primary responsibility is to build and grow AI tools, including a virtual AI expert for each commodity and process, and to integrate these AI advancements into the Suspension University's training and technical maturity models. The role involves managing foundation initiatives, tracking open items, and supporting technical design reviews, with a strong emphasis on improving engineering processes and product quality through AI.