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Tier-1 brand plus a senior ML role with broad GenAI skills yields medium applicant density.
Deep ML/LLM and MLOps expertise required; financial domain experience preferred but not mandatory.
Requires explicit 8–12 years plus mandatory ML/LLM, MLOps, cloud, and production deployment experience.
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Lead end-to-end design, development, and delivery of advanced AI/ML solutions including LLMs, Generative AI, Multimodal AI, and RAG workflows applied to financial analytics.
Partner with Operations, Technology, and business stakeholders to translate complex requirements into scalable data-driven solutions and drive AI platform strategy and adoption.
Own technical quality, best practices, and production deployment of AI models with oversight of MLOps/LLMOps lifecycle and AI governance compliance.
8–12 years experience in data science/AI with strong ownership of complex projects and end-to-end AI/ML lifecycle.
Master's degree in Statistics, Mathematics, Computer Science, or Engineering specialized in Data Science/AI.
Proficiency in Python, ML/DL frameworks, NLP, LLMs, MLOps/LLMOps, and cloud platforms like AWS or Azure.
Work Experience Required: 8–12 years in data science / AI
Experienced in implementing large-scale AI/ML projects in financial services or related domains integrating multiple data types and AI innovations.
Strong technical leadership with ability to act as a technical authority, solve risks, mentor, and influence cross-functional global teams.
Practitioner with deep hands-on skills in advanced AI technologies including LLMOps, AI agents, synthetic data, and modern MLOps and CI/CD deployment practices.