GenAI Specialist

• Expertise in handling  large scale structured and unstructured data.
• Efficiently handled large-scale generative AI datasets and outputs.
• Familiarity in the use of Docker tools, pipenv/conda/poetry env
• Comfort level in following Python project management best practices (use of setup.py, logging, pytests, relative module imports,sphinx docs,etc.,)
• Familiarity in use of Github (clone, fetch, pull/push,raising issues and PR, etc.,)
• High familiarity in the use of DL theory/practices in NLP applications
• Comfort level to code in Huggingface, 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 
• Use of GCP services like BigQuery, Cloud function, Cloud run, Cloud Build, VertexAI, 
• Good working knowledge on other open source packages to benchmark and derive summary
• Experience in using GPU/CPU of cloud and on-prem infrastructures

• 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 in Engineering or Master’s Degree in Computer Science, Engineering, Maths or Science 

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