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
Additional benefits vary by country and will be shared during the hiring process.