Machine Learning Engineer — Risk & AI

Skills

About the Role

You will build, evaluate and deploy machine learning models that detect fraud and protect users, using deep learning and XGBoost. You will improve data quality, features and model performance while balancing fraud detection with customer experience. You will develop AI agents that support investigations, summarize cases, retrieve evidence and automate routine workflows, and use AI coding tools to speed up development, testing and debugging. You will work with engineering, product and risk teams to deploy solutions and monitor their impact.

Requirements

• Strong foundation in machine learning, with hands-on experience in deep learning and tree-based models such as XGBoost or LightGBM
• Strong Python skills and experience training, evaluating, and deploying models
• Some practical experience building AI agents or LLM applications, including tool calling, retrieval, or workflow automation
• Regular use of AI coding tools, with the ability to understand, test, and improve generated code
• Familiarity with databases and data pipelines for preparing training data and supporting ML workflows
• Good problem-solving, communication, and collaboration skills

Responsibilities

• Build, evaluate, and deploy machine learning models for fraud and risk detection
• Improve data quality, features, and model performance, balancing fraud detection with customer experience
• Develop AI agents to support investigations, summarize cases, retrieve evidence, and automate routine workflows
• Use AI coding tools to accelerate development, testing, and debugging while reviewing and validating their output
• Work with engineering, product, and risk teams to deploy solutions and monitor their impact

Benefits

• Performance bonus and long-term incentives may be provided
• L&D programs
• Team building programs and company events
• Wellness and meal allowances
• Comprehensive healthcare schemes for employees and dependants