A leading systematic hedge fund, known for its collaborative, research-driven culture, is seeking a Machine Learning Specialist to apply cutting-edge ML techniques to enhance trading strategies and infrastructure.

This is a first-of-its-kind role, where you will act as a subject matter expert in ML, working across asset classes and strategies to develop scalable, high-impact solutions.

With a highly selective team (predominantly Ivy League/Oxbridge grads) and a multi-strat, multi-asset approach, this firm offers a unique opportunity to shape the future of machine learning in systematic finance.

Key Responsibilities:

• Develop & Apply Machine Learning Solutions: Identify opportunities to integrate ML into alpha generation, execution, and risk management.
• Cross-Team Collaboration: Work with quant researchers, traders, and engineers across equities, macro, and volatility strategies.
• End-to-End Implementation: Own the ML research pipeline, from feature extraction to production deployment.
• Stay at the Cutting Edge: Leverage advancements in deep learning, NLP, reinforcement learning, and other AI techniques to enhance systematic trading.
• Multi-Asset Coverage: Apply ML methodologies across equities, vol (rates/converts), commodities, FX, and credit.

Ideal Profile:

• PhD or Master’s in Machine Learning, Computer Science, Applied Mathematics, or a related field, with a strong publication record in top ML/AI conferences.
• First-Principles Thinker: Ability to craft ML solutions tailored to high-performance trading environments.
• Extensive NLP & Feature Engineering Experience: Strong focus on scalable data analysis for signal generation.
• Strong Programming & ML Stack: Proficiency in Python, TensorFlow, PyTorch, Scikit-learn, and distributed computing.
• Quantitative Finance Exposure: Preference for candidates with quant experience, not just pure AI/ML backgrounds.