ML Scientist - Systematic Trading & AI Research

Durlston Partners; Greater London; On-site; GBP 120,000 - 180,000; Full time

Job summary

Durlston Partners in London seeks a Machine Learning Specialist to advance trading strategies by applying cutting-edge ML techniques across assets. You will own the end-to-end ML research pipeline from feature extraction to production deployment, working with quants, traders, and engineers to improve alpha generation and risk management.

The role emphasizes deep learning, NLP, reinforcement learning, and scalable solutions in a high-performance trading environment; candidates should have a PhD

Qualifications

• PhD or Master’s in Machine Learning, Computer Science, Applied Mathematics, or a related field.
• Strong publication record in top ML/AI conferences.
• Ability to craft ML solutions for high‑performance trading environments.
• Extensive NLP and feature engineering experience.
• Proficiency in Python, TensorFlow, PyTorch, Scikit‑learn, and distributed computing.
• Quantitative finance exposure.

Responsibilities

• Develop and apply machine‑learning solutions; identify opportunities to integrate ML into alpha generation, execution, and risk management.
• Collaborate across teams; work with quant researchers, traders, and engineers across equities, macro, and volatility strategies.
• Own the end‑to‑end ML research pipeline, from feature extraction to production deployment.
• Leverage advancements in deep learning, NLP, reinforcement learning, and other AI techniques to enhance systematic trading.
• Apply ML methodologies across equities, volatility (rates/converts), commodities, FX, and credit.

Skills

Python

TensorFlow

PyTorch

Scikit-learn

NLP

Distributed computing

Quantitative finance exposure

Education

PhD or Master’s in ML/CS/Applied Mathematics

Job description

Durlston Partners in London seeks a Machine Learning Specialist to advance trading strategies by applying cutting-edge ML techniques across assets. You will own the end-to-end ML research pipeline from feature extraction to production deployment, working with quants, traders, and engineers to improve alpha generation and risk management.

The role emphasizes deep learning, NLP, reinforcement learning, and scalable solutions in a high-performance trading environment; candidates should have a PhD