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Tier-1 employer, metro location, popular ML role with broad GenAI skillset increases candidate competition.
Deep GenAI, LLM, and ML Ops requirements limit cross-industry transferability and need specialized expertise.
Explicit 8-13 years plus mandatory GenAI, LLM, and ML tooling skills makes shortlisting highly strict.
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Lead and manage AI and machine learning projects, focusing on Generative AI and large language models like OpenAI, Gemini, and Anthropic.
Implement retrieval-augmented generation (RAG) techniques and optimize AI chatbots and conversational agents using frameworks such as LangFlow and LangChain.
Collaborate with cross-functional teams to deliver scalable, production-ready AI applications, including training and fine-tuning specialized language models.
8 to 13 years of relevant work experience in AI, machine learning, or data science.
Bachelor's or Master's degree in Technology or Engineering (BE, B.Tech, M.Tech) as specified; MBA also mentioned but core technical degree likely primary.
Mandatory technical skills: Generative AI production development, RAG, Vector Database, LangChain, deep learning architectures (CNN, RNN, LSTM, Transformers), strong programming skills in SQL, Python/R, and ML frameworks like PyTorch and TensorFlow.
Experience with AI chatbot development, object-oriented programming, LLM prompt engineering, API usage, and ML Ops for scalable deployment.
Experienced leader in AI/ML project delivery within production environments focusing on generative AI and LLM applications.
Strong technical expertise across AI frameworks, embedding techniques, and scalable model deployment including fine-tuning with LoRA/QLoRA/PEFT.
Comfortable working in hybrid setups, collaborating cross-functionally, and applying advanced text analytics (NLP/NLU/NLG) along with data mining and statistical modeling.