AI Tech Specialist
Ford Motor Company
- 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.
- High familiarity in the use of DL theory/practices in NLP applications
- Comfort level to code in ADK, A2A, AgentSkills, Ontology, Huggingface, LangGraph, LangChain, Chainlit, Tensorflow and/or Pytorch, Scikit-learn, Numpy and Pandas
- Comfort level to use two/more of open source NLP modules like SpaCy, TorchText, fastai.text, farm-haystack, and others
- Knowledge in fundamental text data processing (like use of regex, token/word analysis, spelling correction/noise reduction in text, segmenting noisy unfamiliar sentences/phrases at right places, deriving insights from clustering, etc.,)
- Have implemented in real-world BERT/or other transformer fine-tuned models (Seq classification, NER or QA) from data preparation, model creation and inference till deployment
- 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.