Key Responsibilities:

• Develop, implement, and optimize large language models (LLMs) for applications such as sentiment analysis, news and market signal extraction, data enrichment, and predictive modeling.
• Collaborate with quant researchers and portfolio teams to design AI-driven tools that enhance investment research and trading workflows.
• Handle large-scale structured and unstructured financial datasets to create robust NLP pipelines.
• Continuously improve the performance, efficiency, and scalability of LLMs for real-time use cases.
• Stay ahead of developments in NLP, generative AI, and financial machine learning, ensuring that the team integrates cutting-edge techniques into applied research.
• Deploy ML models into production, integrating seamlessly with research and trading infrastructure.
• Identify and mitigate potential risks in AI models, includin...