Brain AI Researcher

Summary

Join WorldQuant as an AI Researcher and contribute to the development of quantitative models for the BRAIN platform. You will conduct research in AI and LLMs, applying techniques to develop quantitative models. Responsibilities include designing, training, and fine-tuning LLMs and other AI models to extract insights and generate signals. You will analyze large-scale financial datasets to uncover patterns and build models using statistical, mathematical, and machine learning techniques. Collaboration with platform development teams is essential to design and test new functionalities and datasets. Staying updated on the latest advancements in AI and LLM research is crucial to identify opportunities to integrate them into quantitative finance applications.

Requirements

• Strong knowledge and hands-on experience in AI, Machine Learning (ML), and LLMs
• Proficiency in Python and C++
• Familiarity with PyTorch or TensorFlow
• Solid foundation in mathematics, statistics, and quantitative modeling
• Bachelor’s or advanced degree in Computer Science, AI, Mathematics, Financial Engineering, or related fields from a leading university
• Creative problem solver with a passion for experimentation and unsolved challenges
• Strong interest in financial markets
• Ability to work in a team-oriented culture
• Excellent communication and presentation skills in English

Responsibilities

• Conduct research in AI and LLMs, experimenting with advanced architectures such as Transformer models, Reinforcement Learning, and Generative AI
• Design, train, and fine-tune LLMs and other AI models to extract insights, and generate signals
• Apply AI concepts to create and enhance alphas on the BRAIN platform
• Analyze large-scale financial datasets to seek to uncover patterns and build models using statistical, mathematical, and machine learning techniques
• Collaborate with platform development teams to design and test new functionalities and datasets
• Stay updated on the latest advancements in AI and LLM research, identifying opportunities to integrate them into quantitative finance applications

Preferred Qualifications

Experience with financial datasets is a plus