Machine Learning Engineer – Trade Surveillance

About the role

TradingHub is looking for its first dedicated Machine Learning Engineer to strengthen the analytics division of its market‑surveillance platform. You will apply modern large‑language‑model and natural‑language‑processing techniques to complex financial data, helping to detect manipulation and improve trader‑behaviour metrics.

Key responsibilities

• Design, develop and deploy ML models that enhance trade‑surveillance and analytics capabilities.
• Create advanced metrics for analysing trader behaviour, order execution and potential market‑abuse scenarios.
• Apply statistical and deep‑learning techniques to large‑scale financial datasets to improve accuracy and reduce false positives.
• Leverage LLM and NLP models to extract insights from unstructured data and integrate them into existing workflows.
• Collaborate with quantitative developers, data engineers and product teams to productionise models as scalable, high‑performance services.

Required profile

• Strong programming skills in Python and experience with modern ML frameworks.
• Good understanding of core machine‑learning concepts, including linear regression, reinforcement learning and deep learning.
• Hands‑on experience using Large Language Models to deliver commercial value.
• Proven ability to build data pipelines and perform feature engineering on real‑world datasets.
• Keen interest in financial markets such as pricing, trading or fixed income.

Required skills

• Python
• PyTorch
• TensorFlow
• scikit‑learn
• SQL
• LLM
• NLP

What we offer

• Competitive compensation package.
• Opportunity to shape the ML function in a fast‑growing fintech company.
• Collaborative environment with experts in quant research, engineering and product.
• Access to cutting‑edge financial data and modern AI tools.