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.