Staff Machine Learning Engineer - Applied ML & Research

As a Staff Machine Learning Engineer in the Applied ML & Research team, you'll drive the development of machine learning solutions that power critical features across our online gaming platforms. Your work will directly impact platform security, user experience, and large-scale data-driven decision-making for hundreds of thousands of users daily. This role blends hands-on technical work with strategic thinking — you'll lead by example, contribute high-quality code, and help shape the ML roadmap through cross-functional collaboration.

What the role involves

• Identify high-impact ML opportunities and influence stakeholders to prioritise and support these initiatives
• Design and develop scalable machine learning models — including classifiers, regressors, and rule-based systems — to solve real-world problems
• Own the full ML lifecycle: from data exploration and feature engineering to model training, evaluation, and deployment
• Translate complex technical concepts into clear insights for both technical and non-technical stakeholders
• Set and guide technical direction across ML projects, ensuring alignment with technical best practices and business goals
• Mentor junior engineers and foster a culture of knowledge sharing and continuous improvement

What we are looking for

• Master's degree (or equivalent) in Machine Learning, Data Science, Statistics, Mathematics, Computer Science, or a related field
• 7+ years of industry experience building and deploying ML models at scale
• Proven ability to lead cross-functional technical initiatives and influence engineering strategy
• Proficiency in Python (with libraries such as PyTorch, XGBoost, and Scikit-learn) and SQL
• Strong experience with machine learning pipelines and orchestration tools such as Airflow, SageMaker Pipelines, or similar
• Deep understanding of machine learning fundamentals, including experience with Large Language Models (LLMs) and other emerging ML technologies
• A track record of shipping production-level ML products and maintaining high code quality
• Excellent problem-solving skills and the ability to scope and disambiguate complex ML projects into clear, achievable milestones

Nice to have

• Familiarity with ML tooling such as MLflow, ZenML, or Metaflow
• Hands-on experience with AWS services (e.g., EC2, EKS, CloudFormation, Cognito)
• Exposure to streaming data platforms such as Kafka
• Contributions to open-source ML projects or publications in ML conferences

What we offer

• Medical / Health Insurance
• Open Annual Leave
• Employee Assistance Programme
• Training & Learning Development