Overview
We are looking for a Machine Learning Engineer to design, build, and deploy models and systems that support trading and research.
This role focuses on applying machine learning in a practical, market-facing context — working with real data, real constraints, and live strategies across financial and event-driven markets.
You will be responsible for turning ideas into production-ready systems that contribute directly to decision-making and performance.
What You’ll Do
Develop and deploy machine learning models for prediction, classification, and optimisation
Work with large, structured and unstructured datasets across multiple markets
Build and maintain data pipelines, feature engineering workflows, and model infrastructure
Integrate models into trading and research systems
Monitor model performance and iterate based on real-world outcomes
Collaborate with traders and researchers to translate ideas into implementable solutions
What We’re Looking For
Strong foundation in machine learning, statistics, and data analysis
Experience building and deploying models in a production environment
Proficiency in Python and common ML libraries
Ability to work with messy, real-world data and imperfect signals
Strong problem-solving skills and attention to detail
We value individuals who can move from concept to implementation with clarity and discipline.
What You’ll Gain
Direct exposure to how machine learning is applied in live trading environments
The opportunity to work on problems where data, speed, and decision-making intersect
Experience building systems that operate under real constraints and uncertainty
A high level of ownership and responsibility
Environment
Small, focused team
Close collaboration across trading, research, and engineering
Emphasis on practical outcomes over theoretical work
Performance-driven, but collaborative
