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Tier-1 brand, metro location, mid-level ML role with broad GenAI skills creates high applicant competition.
Strong ML/GenAI skill requirements but transferable across industries, with preference for regulated-finance experience.
Explicit 3+ years plus mandatory agentic/LLM production and MLOps experience enforces high shortlisting strictness.
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Design, develop, and deploy predictive ML, advanced analytics, and GenAI/LLM agentic AI solutions for Consumer & Community Banking Control Management Shared Services to improve risk control operations.
Own end-to-end delivery of ML models and AI services, including dataset preparation, training, validation, deployment, monitoring, and iteration with production-grade reliability and compliance.
Collaborate with product, engineering, and risk teams to define requirements and integrate reusable AI services that scale across control workflows and support regulatory/change management processes.
Bachelor's degree in data science, computer science, statistics, mathematics, or related field (or equivalent experience).
3+ years experience setting up and deploying AI/ML solutions end-to-end (prototype to production), including predictive modeling and NLP.
Strong proficiency in Python and hands-on experience with ML/deep learning frameworks (PyTorch, TensorFlow, scikit-learn).
Experience building and deploying LLM-enabled agentic workflows (e.g., retrieval-augmented generation, tool use, routing/planning) with evaluation approaches and production ML pipelines including MLOps practices.
Experienced in scalable GenAI/agentic AI systems with proven evaluation and guardrail frameworks for production deployment.
Comfortable working in cloud/containerized environments (AWS/Azure/GCP, Kubernetes) applying ML/LLM pipelines within regulated financial services or similar compliance-focused domains.
Capable of translating complex business risk and control challenges into measurable technical AI solutions and partnering effectively across multidisciplinary teams.