Job Description

About the Firm This firm is a technology-driven hedge fund that applies machine learning and AI to develop systematic investment strategies. With a unique approach that combines crowdsourced data science and cutting-edge quantitative research, the firm is at the forefront of AI-driven investing. Researchers have access to massive proprietary datasets, high-performance computing infrastructure, and a collaborative research environment, where new ideas can be rapidly tested and deployed in live markets. The Role As the LLM Quantitative Research Lead, you will lead the effort to develop, fine-tune, and apply state-of-the-art LLM methodologies to financial prediction. You will work with high-dimensional, structured and unstructured datasets to extract meaningful patterns and design novel AI-driven investment strategies. Key Responsibilities Research and develop cutting-edge LLM methodologies for financial markets, leveraging self-supervised learning, reinforcement learning, and transfer learning techniques. Build and optimize deep learning architectures to extract alpha from structured and unstructured financial data (e.g., news, filings, alternative datasets). Collaborate with world-class quantitative researchers, data scientists, and engineers to integrate AI-driven insights into systematic trading strategies. Stay ahead of advancements in deep learning, NLP, and generative AI, evaluating their applications in finance. Work in a research-first environment where experimentation, innovation, and rigorous testing drive strategy development. What We're Looking For Ph.D. in AI, Machine Learning, Computer Science, or a related quantitative field from a top institution. Extensive experience in LLM research, deep learning, and advanced NLP techniques. Strong programming skills in Python and experience with ML frameworks such as PyTorch, TensorFlow, or JAX. Expertise in training and fine-tuning large-scale transformer models, working with massive, high-dimensional datasets. A passion for applying cutting-edge AI research to real-world problems-financial experience is not required, but curiosity and a desire to learn are essential. Strong problem-solving skills and the ability to work in a fast-paced, research-driven environment. Why Apply? Opportunity to pioneer the use of LLMs in finance, working at the intersection of AI and quantitative investing. Access to proprietary financial datasets, high-performance compute infrastructure, and a highly collaborative research environment. Work with a team of world-class AI researchers and quants, solving some of the hardest problems in systematic investing. A research-driven culture that values innovation, experimentation, and independent thinking.

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