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Tier-1 brand and metro role attracts many applicants, balanced by niche GenAI/NLP requirements.
Specialized GenAI/NLP skills are transferable across industries, though retail product-matching preference increases sensitivity.
Explicit 7+ years requirement plus deep ML/GenAI, LLM, and cloud/engineering skills required.
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Lead design, development, productionization, and maintenance of AI/ML systems for Competitive Product Classification, Matching and Validation.
Own technical strategy and execution for specific problem areas, influencing roadmaps and quality standards across teams.
Architect scalable end-to-end AI/ML solutions integrating modeling, experimentation, and engineering systems including transformer models and RAG pipelines.
Bachelor's degree in a quantitative discipline (Science, Technology, Engineering, Mathematics) or equivalent experience.
7+ years professional experience in data science or applied machine learning with production-scale AI/ML system delivery.
Strong expertise in modern ML techniques including deep learning, NLP, GenAI, and Agentic AI, with experience in Transformers, LLMs, RAG, and multi-agent systems.
Proficiency in Python, SQL, Spark, and familiarity with cloud platforms like GCP for model lifecycle and online inference tooling.
Experienced leader able to manage large, ambiguous AI/ML problem spaces, driving alignment and delivery through cross-functional teams.
Deep domain knowledge in NLP, Deep Learning, GenAI, Agentic AI, and search or information retrieval for e-commerce or consumer products.
Proven ability to handle LLM adaptation, agentic workflows, prompt engineering, and build evaluation frameworks for complex AI systems.