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Tier-1 brand, mid-level ML role in Bangalore with broad requirements increases candidate competition.
Role requires specialized ML/LLM and MLOps skills, but skills are moderately transferable across industries.
Requires mandatory ML/LLM production experience, MLOps, and cloud skills, making screening highly selective.
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Design, develop, and deploy predictive ML, advanced analytics, GenAI/LLM, and agentic AI solutions to support Consumer & Community Banking Control Management across multiple business functions.
Own end-to-end model lifecycle including dataset preparation, training, validation, deployment, and iteration for AI/ML solutions integrated into risk and control management workflows.
Build reusable, production-ready AI services with measurable business impact, ensuring governance, monitoring, and compliance alignment, while partnering with stakeholders for adoption and success metrics.
Bachelor’s degree in data science, computer science, statistics, mathematics, or a related technical field (or equivalent practical experience).
At least 3 years of experience in end-to-end AI/ML solution deployment from prototype to production including agentic AI workflows with LLM integration.
Strong proficiency in Python, hands-on experience with ML/deep learning libraries (PyTorch, TensorFlow, scikit-learn), and experience in production ML/LLM pipeline operations including MLOps practices.
Working knowledge of modern deployment environments such as cloud platforms (AWS/Azure/GCP) and containerized/distributed compute (e.g., Kubernetes).
Experienced with building and scaling agentic AI systems involving LLM-enabled workflows with robust evaluation methodologies and guardrails.
Demonstrates ability to translate complex business problems in banking control environments into technical AI solutions with measurable outcomes and stakeholder alignment.
Background or comfort operating within regulated environments, particularly in financial services, with focus on governance, compliance, and audit-ready implementations.