Machine Learning Engineer

Responsibilities

Design, build, and deploy production-grade ML models to solve core business challenges, including: - Personalization & Recommendation Engines – deliver personalized game recommendations, bonuses, and content for millions of players; - Player Churn Prediction – identify at-risk players and enable proactive retention campaigns; - Lifetime Value (LTV) Forecasting – forecast long-term player value to optimize user acquisition spend; - Marketing Mix Models (MMM) – measure marketing channel impact and guide budget allocation.
Own the entire ML lifecycle: from problem definition and data exploration to deployment, monitoring, and iteration.
Build scalable and reliable data pipelines for training and inference in collaboration with data engineering.
Translate business needs into ML solutions, working closely with product managers, marketing specialists, and analysts.

3+ years of hands-on experience building and deploying ML models in production;
Strong knowledge of ML fundamentals (regression, classification, clustering, and trade-offs between modeling approaches);
Expert-level Python with core ML/DS libraries (pandas, NumPy, scikit-learn, XGBoost);
Experience with deep learning frameworks (TensorFlow, PyTorch), ideally for recommendation systems;
Solid SQL skills for complex data manipulation and feature engineering;
Practical experience with MLOps tools and practices (MLflow, Kubeflow, Docker, CI/CD);
Familiarity with data workflow tools (Airflow, Spark or similar);
MSc or PhD in Computer Science, Statistics, or a related quantitative field;
Experience in iGaming, e-commerce, or mobile gaming is a strong plus;
Engineering mindset: you write clean, maintainable, and tested code, with a focus on scalability and reliability.

Remote-first work environment;
Competitive salary (discussed during the interview process);
Fully covered vacation and sick leave;
Work equipment provided;
5/2 schedule with flexible working hours;
Benefits package (sports, healthcare, education);
An opportunity to make a tangible impact and full support for your ideas and initiatives.

Our recruiters carefully review your application and reach out to schedule the initial interview. Feel free to ask more about the role!

Candidates selected undergo an interview where we discuss their skills, experience, and how they fit with corporate culture.

Some candidates might complete a task to show their skills in action. Usually brief, these tasks respect your time.

This is the last step where you get feedback on your task and meet our department head.

We decide within 2 weeks and notify the chosen candidate with an offer to join us!