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Tier-1 brand and Pune metro raise interest, but senior, niche KYC ML specialization reduces applicant density.
Requires deep KYC/AML and regulated-finance expertise, making skills less transferable across industries.
Explicit 10+ years, KYC/financial crime domain and strong ML/MLOps requirements enforce stringent shortlisting.
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Lead the strategy, design, and development of advanced AI Agents and ML models to improve operational efficiency and accuracy in KYC processes such as onboarding, due diligence, and transaction monitoring.
Own end-to-end delivery of complex AI/ML projects independently, including design, development, testing, deployment, and ongoing optimization in a regulated financial environment.
Provide expert mentorship and lead adoption of best practices for AI/ML agent engineering, ensuring solutions are scalable, secure, explainable, and compliant with financial regulations.
10+ years of AI/ML engineering experience with significant exposure to financial services, KYC, or financial crime prevention domains.
Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or related quantitative field.
Expert proficiency in Python and AI/ML libraries such as TensorFlow, PyTorch, SpaCy, Hugging Face, and Scikit-learn, plus hands-on experience with MLOps platforms and CI/CD pipelines.
Strong domain knowledge of KYC processes, AML regulations, financial crime prevention, and experience with big data technologies (Spark, Hadoop, Kafka) and cloud platforms (AWS, Azure).
Experienced in independently driving full lifecycle AI/ML projects in highly regulated financial or FinTech environments, especially related to KYC and compliance.
Skilled in applying NLP, knowledge graphs, anomaly detection, and explainable AI techniques tailored to financial crime and regulatory requirements.
Capable of collaborating cross-functionally with compliance, risk, and operations teams while mentoring engineering peers on complex AI/ML agent development.