AI Tech Specialist

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.

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

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.,)