ML Quant

Job description / Role

Job description

We are seeking a highly skilled machine learning quant to join a leading multi-strategy hedge fund. This role involves designing and implementing robust ML systems and infrastructure to support systematic trading strategies. You will leverage a wide range of machine learning techniques including classical ML, deep learning, and generative AI to develop predictive models and optimise trading performance.

Key responsibilities

• Design and build scalable ML infrastructure for real-time trading environments.
• Develop and deploy machine learning models for alpha generation and risk management.
• Collaborate with researchers, engineers, and traders to integrate ML solutions into production systems.
• Explore and apply advanced techniques (e.g., reinforcement learning, probabilistic modelling, generative AI) to enhance systematic strategies.
• Ensure system reliability, low latency, and compliance with best practices in software engineering.

Qualifications

• Masters degree in computer science, mathematics, statistics, or related field (PhD preferred).
• Strong programming skills in Python, C++, or similar languages.
• Expertise in machine learning frameworks (TensorFlow, PyTorch, scikit-learn).
• Solid understanding of quantitative finance and systematic trading principles.
• Experience with distributed systems and cloud-based ML infrastructure.
• Excellent problem-solving skills and ability to work in a fast-paced environment.

Preferred experience

• Prior experience in a hedge fund, proprietary trading firm, or similar environment.
• Familiarity with time-series modelling and financial data.
• Knowledge of reinforcement learning and Bayesian inference techniques.