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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 secure diffusion, Instruct pix2pix. - Expertise in handling large scale structured and unstructured data. - Efficiently handled large-scale generative AI datasets and outputs. ML/DL Skills: - 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 NLP Skills: - 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 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. Experience: 8+ Education: Bachelors or Masters Degree in Computer Science, Engineering, Maths or Science Performed any modern NLP/LLM courses/open competitions is also welcomed. .