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Tier-1 brand, popular Data Scientist title, and Bangalore location increase candidate competition.
Core GenAI and LLM skills are broadly transferable across industries; domain experience is optional.
Explicit 5–8 year requirement and mandatory GenAI toolset make filters strict.
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Design, develop, test, and deploy state-of-the-art machine learning models with a strong focus on language models and Generative AI solutions.
Lead and independently handle AI/ML projects including building end-to-end NLP solutions such as Conversational AI, document understanding, and QnA.
Analyze data to extract business insights, develop new metrics, and translate analytic findings into actionable recommendations for product improvements.
5 to 8 years of experience as Data Scientist or GenAI specialist with 2 to 3 years in Generative AI solution development.
Proven experience and hands-on skills with GenAI technologies including open-source LLMs (Llama, Gemma, Mixtral), closed source LLMs (OpenAI GPT, Azure OpenAI, Claude, Gemini), and GenAI frameworks like LlamaIndex, Langchain, Autogen.
Strong expertise in NLP algorithms, transformer architectures (BERT, Phi3), machine learning frameworks (Python, Tensorflow, PyTorch) and cloud services (Azure, GCP, AWS).
Experience leading projects technically and directing teams; good communication skills to convey data insights across organizational levels.
Has strong expertise with large language models and related technologies such as RAG, Agents, VectorDB, and Guardrails indicating high technical depth in GenAI.
Experienced in independently handling and leading AI/ML projects, able to design solutions end-to-end and influence stakeholders.
Comfortable working with open-source tools and cloud platforms, and capable of bridging technical implementations with strategic product insights via concise communication.