AI Lab

🤖 AI Researcher / Machine Learning Scientist | London / New York / SingaporeA leading proprietary trading firm is expanding its global footprint with the launch of a new AI Research Lab across London, Singapore, and New York. The initiative focuses on applying cutting-edge artificial intelligence and machine learning to solve complex market prediction, trading optimization, and large-scale data challenges.This is a unique opportunity to join a cross-disciplinary research team at the intersection of quantitative finance, data science, and AI — where innovation directly drives trading performance.Key Responsibilities:Research, develop, and deploy AI-driven models to identify trading opportunities and improve decision-making.Apply machine learning, deep learning, reinforcement learning, and NLP techniques to large, high-frequency datasets.Collaborate with quant researchers, traders, and engineers to integrate models into live trading environments.Conduct exploratory research into emerging ML techniques, optimizing both model performance and interpretability.Leverage modern compute infrastructure for large-scale experimentation and production deployment.Core Skills & Experience:Minimum of a Master’s degree (PhD preferred) in Computer Science, Machine Learning, Mathematics, Statistics, Physics, or Engineering.Proven expertise in AI / ML research and development, including model training, validation, and deployment.Strong programming skills in Python and frameworks such as PyTorch, TensorFlow, or JAX.Deep understanding of data processing, feature engineering, and model optimization.Experience with time-series modeling, forecasting, or reinforcement learning highly desirable.Preference for candidates with quant trading, systematic research, or financial modeling experience.Exceptional candidates from Big Tech AI / ML divisions will also be considered.Curiosity-driven mindset with the ability to translate complex research into practical, scalable applications.💡 This is an opportunity to be part of a global AI research initiative within a high-performance trading environment — leveraging cutting-edge research to shape the future of algorithmic decision-making.