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Tier-1 employer, metro location, and mid-level ML role increase candidate density and competition.
Core GenAI/ML skills transfer across industries, though financial services domain knowledge is beneficial.
Explicit 5–8 years plus specific GenAI, LLM, MLOps and deep learning requirements enforce strict filtering.
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Own end-to-end delivery of AI-powered products including requirements gathering, design, implementation, testing, deployment, and support.
Apply advanced Generative AI techniques (prompt engineering, RAG, fine-tuning) and deep learning to solve business problems focused on client experience and operations.
Collaborate with cross-functional teams (product, data, security, platform) to translate ambiguous problems into production-grade AI applications with clear documentation and governance.
5-8 years of experience in Data Science (ML and DL) with solid expertise in Generative AI solutions.
Hands-on experience with LLMs and transformer architectures including prompt engineering, retrieval-augmented generation, model customization, and related frameworks (PyTorch/TensorFlow, Hugging Face).
Master's degree in Computer Science Engineering preferred.
Experience shipping AI-enabled products into production within an agile environment.
Experienced in applying AI/ML solutions to complex business problems in financial services, specifically around client experience and operations.
Able to manage full AI product lifecycle including quality, safety, monitoring, and compliance.
Skilled at collaborating across business, product, data science, and engineering teams to deliver scalable, secure, and well-documented Generative AI applications.