Description

You design and build agentic Generative AI frameworks for Capital Markets use cases, owning the architecture, model development, and MLOps lifecycle.

This role is on-site.

Responsibilities

• Design and implement agentic Generative AI frameworks for summarization, research insights, and information extraction.
• Embed LLM-based solutions into existing Capital Markets platforms and lead AI experimentation with hypothesis testing.
• Manage end-to-end MLOps, including deployments, monitoring, and performance tracking in regulated environments.
• Guide the team through design reviews, code reviews, and AI best practices.

Required Skills

• 7+ years of hands-on experience building Machine Learning and Deep Learning models.
• In-depth expertise in Generative AI, Natural Language Processing (NLP), and Information Extraction.
• Strong experience with Embeddings, re-rankers, retrieval-augmented generation (RAG), and agentic frameworks.
• Proficiency in inference optimization, fine-tuning strategies, and model architectures.
• Strong understanding of Algorithms and Data Structures.
• Knowledge of distributed computing systems.
• Proven ability to act as the primary technical contributor while mentoring others.

Preferred Skills

• PhD or master’s degree in computer science, Machine Learning, or Deep Learning.
• Experience working in regulated financial environments.

Key Skills

Education

Bachelor's or Master's degrees