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Tier-1 brand, mid-level ML title, metro location, and broad generalist skillset create high candidate competition.
Role requires specialized ML and Generative AI expertise, limiting transferability across non-AI domains.
Multiple explicit years plus mandatory ML, Generative AI, LLM and framework expertise enforces highly strict filters.
Collaborate with business stakeholders to translate complex challenges into scalable data science and Generative AI solutions.
Design, build, validate, and deploy machine learning models and autonomous AI agent systems leveraging frameworks like Google ADK, LangGraph, LangChain.
Manage end-to-end model lifecycle including data preparation, feature engineering, deployment, monitoring, and optimization ensuring data quality and responsible AI practices.
Bachelor's degree in Data Science, Computer Science, Statistics, Applied Mathematics, Operations Research, Engineering, or related quantitative field.
Minimum 4 years hands-on experience in machine learning techniques (regression, classification, clustering, decision trees, random forests, SVMs).
4+ years of Python programming experience using libraries such as Pandas, NumPy, Matplotlib, Seaborn, plus 4+ years SQL experience.
At least 2 years experience developing Generative AI applications with prompt engineering, RAG, embeddings, or model fine-tuning; experience with AI agent frameworks like Google ADK, LangGraph, or LangChain.
Experienced individual contributor capable of independently delivering end-to-end data science and Generative AI solutions within business contexts.
Strong technical expertise with advanced skills in both classical machine learning and Generative AI technologies, including agentic workflows.
Comfortable working cross-functionally to interpret business problems into technical solutions and communicate findings effectively to technical and non-technical audiences.