AI Tech Specialist
- Job ID
- 67147
- Category
- Global Data Insight & Analytics
- Location
- Chennai, India
- Work Type
- Hybrid
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:
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: Bachelor’s or Master’s Degree in Computer Science, Engineering, Maths or Science
Performed any modern NLP/LLM courses/open competitions is also welcomed.
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