AI Engineer

Ford Artificial Intelligence Advancement Center is looking for professionals experienced in NLP/LLM/GenAI, who are hands-on and can employ many NLP/Prompt engineering techniques from traditional statistical/ML NLP to DL-based sequence models and transformers in their day-to-day work.

You'll be working alongside leading technical experts from all around the world, on a variety of products involving Sequence/token classification, QA/chatbots, translation, semantic/search and summarization, among others.

Responsibilities:

• Design NLP/LLM/GenAI applications/products by following robust coding practices, 

• Explore SoTA models/techniques so that they can be applied for automotive industry usecases

• Conduct ML experiments to train/infer models; if need be, build models that abide by memory & latency restrictions, 

• Deploy REST APIs or a minimalistic UI for NLP applications using Docker and Kubernetes tools

• Showcase NLP/LLM/GenAI applications in the best way possible to users through web frameworks (Dash, Plotly, Streamlit, etc.,)

• Converge multibots into super apps using LLMs with multimodalities

• Develop agentic workflow using Autogen, Agentbuilder, langgraph

• Build modular AI/ML products that could be consumed at scale.

Education: Bachelor’s or Master’s Degree in Computer Science, Engineering, Maths or Science 

Performed any modern NLP/LLM courses/open competitions is also welcomed. 

Soft Skills: 

• Strong communication skills and do excellent teamwork through Git/slack/email/call with multiple team members across geographies

GenAI Skills: 

• Experience in LLM models like PaLM, GPT4, Mistral (open-source models), 

• Work through the complete lifecycle of Gen AI model development, from training and testing to deployment and performance monitoring.

• Developing and maintaining AI pipelines with multimodalities like text, image, audio etc. 

• Have implemented in real-world Chat bots or conversational agents at scale handling different data sources.  

• Experience in developing Image generation/translation tools using any of the latent diffusion models like stable diffusion, Instruct pix2pix. 

• Expertise in handling  large scale structured and unstructured data.

• Efficiently handled large-scale generative AI datasets and outputs.