As a Senior Machine Learning Engineer, you’ll play a key role in building and scaling Axi’s data-driven trading capabilities. You’ll focus on developing machine learning models and quantitative frameworks using large-scale datasets, helping uncover insights that drive smarter trading and risk decisions.
This is a hands-on technical role at the intersection of machine learning, data engineering, and quantitative research — ideal for someone who enjoys working with complex datasets and translating them into real-world impact.
What you’ll do
- Design and build machine learning models using large-scale datasets (millions to billions of rows), including time-series and event-driven data
- Analyse client behaviour, flow data, and market signals to uncover actionable insights
- Develop data-driven approaches to support trading strategies, risk optimisation, and execution efficiency
- Work with structured and unstructured datasets to identify patterns, anomalies, and predictive signals
- Collaborate with trading, product, and engineering teams to translate models into production-ready solutions
- Evaluate model performance using historical and real-time data, ensuring robustness and scalability
- Continuously improve modelling approaches, feature engineering, and data pipelines
- Contribute to building a scalable quantitative and machine learning ecosystem within the firm
What we’re looking for
- Strong experience in machine learning / data science, particularly working with large and complex datasets
- Proven experience building models using time-series data or high-frequency/event-driven datasets
- Solid foundation in statistics, predictive modelling, and data analysis
- Strong hands-on programming skills in Python
- Experience working with data at scale (e.g. distributed systems, large databases, or streaming data)
- Ability to work independently, prioritise effectively, and deliver high-quality technical solutions
Nice to have (but not required)
- Exposure to trading, financial markets, or quantitative finance concepts
- Experience working with client behaviour / segmentation / transaction data
- Familiarity with kdb+ / KDB or other time-series databases
- Understanding of systematic trading or execution strategies