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Metro location and broad ML/LLM skillset increase applicant density despite niche surveillance domain.
Advanced ML skills transferable, but surveillance and regulated banking domain require specialized experience.
Explicit 7-12 years and mandatory ML, Databricks, PyTorch/TensorFlow, and MLflow requirements.
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Design, develop, train, fine-tune, and deploy AI/ML models focused on Communication Surveillance to detect regulatory breaches, market abuse, and employee misconduct across multiple communication channels.
Build and optimize advanced NLP and Large Language Model solutions using Databricks and MLflow for production-grade surveillance applications in a regulated financial environment.
Manage end-to-end model lifecycle including experiment tracking, deployment, monitoring, and ensure compliance with regulatory standards.
7-12 years of overall IT experience.
Strong expertise in Machine Learning, Deep Learning, Natural Language Processing (NLP), Large Language Models (LLMs), and Generative AI.
Proficient programming skills in Python with hands-on experience in PyTorch and TensorFlow.
Experience with Databricks Lakehouse Platform and MLflow for model management and deployment.
Experienced in deploying AI/ML solutions in highly regulated Banking and Capital Markets domains, especially communication and trade surveillance.
Skilled in building scalable, production-ready NLP and LLM solutions within enterprise-grade compliance frameworks.
Proficient collaborating with cross-functional stakeholders including compliance and domain experts to translate business requirements into AI models.