Senior ML Engineer

Our client – is a company that creates innovative solutions for the iGaming industry, focusing on player engagement and retention. It develops loyalty programs with gamification elements, implements online streaming, and helps brands enhance their visibility and efficiency. With a comprehensive approach, the company transforms user experience and strengthens customer loyalty. More than 20 brands from 18 countries already use its ecosystem.

• 5+ years of hands-on experience in software engineering or machine learning engineering
• Strong proficiency in Python and common ML libraries (pandas, NumPy, scikit-learn, PyTorch, TensorFlow)
• Practical experience with cloud infrastructures such as AWS, GCP, or Azure, as well as containerization technologies (Docker, Kubernetes)
• Proven experience working with MLOps tools and platforms (e.g. MLflow, Kubeflow, Airflow, SageMaker, Vertex AI)
• Solid understanding of data engineering concepts, including ETL pipelines, batch and streaming data processing
• Strong foundation in algorithms, data structures, and distributed systems
• Experience deploying, scaling, and monitoring machine learning models in production
• Excellent analytical thinking, problem-solving abilities, and communication skills

• Build, maintain, and optimize end-to-end machine learning pipelines, from data ingestion and preprocessing to model deployment and monitoring
• Partner closely with data scientists to transition models from experimentation to production-ready systems
• Ensure high availability, scalability, and performance of ML services in production environments
• Develop and maintain tooling for experiment tracking, model versioning, and reproducibility
• Work with large-scale data platforms such as Spark, Hadoop, Snowflake, or Redshift
• Apply MLOps best practices, including CI/CD pipelines for ML, model monitoring, and automated retraining workflows
• Review code, mentor junior engineers, and actively contribute to technical discussions and architectural decisions

• Two collaboration hubs located in Warsaw, Poland, and Kyiv, Ukraine
• Flexible working hours to support work-life balance
• Paid time off including 20 days for rest and recovery
• Additional 14 days of paid leave for health-related needs
• Structured onboarding and professional support during the first months, guided by experienced team members
• Team-building events and engaging corporate activities
• Competitive compensation package