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Tier-1 brand and Bangalore metro boost candidate volume, but senior, niche ML/LLM specialization moderates competition.
Core ML/AI skills are transferable but financial domain knowledge and governance increase fit sensitivity.
Explicit 8–12 years plus specialized LLM, MLOps, cloud, and production AI requirements enforce strict filters.
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Lead end-to-end AI/ML initiatives including design, development, and scalable deployment of advanced models (LLMs, Generative AI, multimodal).
Collaborate with business and technology stakeholders to translate requirements into data science solutions and influence cross-functional AI strategy.
Own technical quality, best practices, and innovation for data science frameworks and ML lifecycle management including MLOps/LLMOps and cloud deployment.
8–12 years of experience in data science/AI with strong ownership of complex AI/ML projects.
Master’s degree in Statistics, Mathematics, Computer Science, or Engineering specialized in Data Science/AI.
Deep expertise in Python, ML/DL frameworks, NLP, LLMs, RAG workflows, production MLOps/LLMOps, and cloud platforms (AWS/Azure).
Work Experience Required: 8–12 years in data science/AI domain.
Experienced in delivering production-grade AI/ML solutions in large-scale, complex environments, especially financial services preferred but not mandatory.
Able to function as a technical authority resolving risks, mentoring teams, and defining robust evaluation and compliance frameworks (Responsible AI).
Proficient in advanced AI technologies including Generative AI, AI agents, synthetic data, and LLM lifecycle orchestration tools, demonstrating strategic and innovative leadership.