Key Responsibilities:
Research, develop, and deploy Generative AI models for enterprise-scale use cases in capital markets.
Design and optimize architectures involving RAG, fine-tuning, and multi-model orchestration.
Apply zero-shot and few-shot learning using foundation models and prompt engineering strategies.
Collaborate with engineering, data science, and product teams to productionize AI capabilities.
Monitor model performance, conduct A/B testing, and ensure model robustness and compliance.
Must-Have:
3+ years of experience in applied AI/ML, including recent hands-on work with LLMs, transfer learning, and Generative AI architectures.
Strong understanding of transformer-based models and deep learning frameworks.
Experience with RAG systems, model fine-tuning, and large-scale deployment.
Proficiency in Python, PyTorch, Hugging Face Transformers, and modern MLOps practices.
Familiarity with scalable system design for AI/ML workflows.
Experience in financial services, capital markets, or enterprise data platforms.
