Machine Learning Engineer - Fast Trading Strategies (New York)

at  Man Group plc

THE TEAM

AHL’s Fast Trading Strategies (FTS) team is responsible for the development of high Sharpe, high-frequency trading strategies across all asset classes. The team has been running for over a decade, and currently manages a large and successful portfolio across both global futures and cash markets. The FTS team is responsible for the full end to end development of the fast alpha portfolio, using a number of techniques to capture fast alphas, ML, event driven, microstructure based etc, building its own customised monetisation stack, and optimising trading and order placement with dedicated high frequency infrastructure.

CURRENT OPPORTUNITIES

We are seeking highly motivated individuals with a strong background in highly technical domains for various opportunities across the FTS team in both London and New York. Individuals of varying levels of experience (across both professional work experience and education levels from Bachelor’s to Doctorate degree) will be considered and matched to a role within FTS according to their skillset, interest and current team needs. Therefore, we would kindly request candidates submit only one application to the Fast-Trading Strategies team’s openings.
We look for researchers and engineers sharing our values of excellence, drive, meritocracy, and integrity.
In return, you will be provided with the opportunity to work with industry experts and experience cutting-edge commercial quantitative finance research in one of the world’s leading systematic hedge funds.

Hiring requirements

• A strong academic background with a degree in a quantitative subject (e.g. Computer Science, Engineering, Physics, Applied Mathematics) from a leading university.
• Further degrees or postdoctoral roles are beneficial although not a requirement.
• Experience with either third-party or in-house research frameworks.
• A passion for highly efficient software to expedite both research and trading strategies.
• A clear and demonstrable interest in financial markets modelling and investing.
• Intellectual curiosity and a willingness to continuously learn and grow.
• Intermediate skills in at least one low-level programming language (e.g. C++, C, Java, Rust).
• The ability to communicate complicated ideas in a clear and concise manner

Machine learning engineers within FTS are responsible for architecting and developing a state-of-the-art turnkey research infrastructure and subsequently collaborating with quantitative researchers to leverage that infrastructure to research and develop highly profitable, fully systematic strategies.

Specific responsibilities will include:

• Building domain knowledge in liquid financial markets.
• Organising research pipelines with both third-party and in-house solutions.
• Streamlining FTS research workflows into cloud and on-prem research clusters.
• Implementing and integrating cutting edge ML and AI models for custom use.
• Serving finished ML models in production trading with low latency and high fidelity.
• Constructing novel features from orthogonal ideas and datasets.
• Back-testing signals to predict the movements of markets over time horizons spanning from minutes to days.
• Engaging in peer-review of research from across the team, and AHL more widely, to help drive top-quality research across the firm.
• Working with our technologists to help improve our trading platform and infrastructure.

Hiring requirements

• A strong academic background with a degree in a quantitative subject (e.g. Computer Science, Engineering, Physics, Applied Mathematics) from a leading university.
• Further degrees or postdoctoral roles are beneficial although not a requirement.
• Experience with either third-party or in-house research frameworks.
• A passion for highly efficient software to expedite both research and trading strategies.
• A clear and demonstrable interest in financial markets modelling and investing.
• Intellectual curiosity and a willingness to continuously learn and grow.
• Intermediate skills in at least one low-level programming language (e.g. C++, C, Java, Rust).
• The ability to communicate complicated ideas in a clear and concise manner.