Ford is seeking to leverage Generative AI and Retrieval-Augmented Generation (RAG) systems to enhance user experience and automate complex processes across the organization.
Requirements
- 3+ years of experience in software engineering with a focus on Generative AI, Machine Learning, or related AI fields.
- Experience deploying AI/ML models into production environments at scale.
- Experience with Retrieval-Augmented Generation (RAG) systems.
- Experience with vector databases.
- Experience with API development frameworks like FastAPI.
- Experience with containerization technologies (e.g., Docker).
- Experience with MLOps practices.
Responsibilities
- Design, develop, and deploy cutting-edge Generative AI solutions, with a particular emphasis on Retrieval-Augmented Generation (RAG) systems.
- Implement and optimize RAG systems, including the selection and integration of appropriate vector databases.
- Develop robust and scalable APIs using frameworks such as FastAPI to support AI-powered applications.
- Ensure efficient and reliable deployment of AI models and applications through containerization technologies (e.g., Docker) and MLOps practices.
- Apply prompt engineering techniques to effectively interact with Large Language Models (LLMs) and optimize their performance.
- Contribute to the fine-tuning of Machine Learning models to meet specific project needs.
- Utilize Python programming and SQL for data manipulation, querying, and model development.
Other
- Collaborate with cross-functional teams to understand requirements and translate them into technical specifications for AI solutions.
- Stay up-to-date with the latest advancements in Generative AI, LLMs, and RAG technologies.
- Previous experience in a large enterprise or fast-paced technology environment.
- Visa sponsorship is available for this position.
- This position is hybrid. Candidates who are in commuting distance to a Ford hub location will be required to be onsite four or more days per week.
