Senior Machine Learning Engineer - Remote

Overview

Scorum Group is an international product company in the gambling sector. We specialize in B2B services, delivering two primary products, Aviatrix and ZingBrain AI. Our mission is to empower gambling businesses worldwide by streamlining their operations and elevating the player experience with groundbreaking features.

In Short

• Design and improve algorithms for personalized sportsbook and casino game suggestions.
• Develop models for lifetime value (LTV), churn, and segmentation to help refine retention strategies.
• Ensure machine learning models are production-ready, scalable, and reliable.
• Build systems that enable dynamic, on-the-fly personalization for players.
• Work closely with data engineers to maintain smooth data pipelines for training and deploying models.
• Use A/B testing and experiments to validate your models’ business impact and refine them.
• Work closely with data scientists on algorithms and approaches for business problems and adopt them for clients.

Requirements

• 3+ years working on machine learning projects, particularly in recommendation systems or predictive modeling.
• 5+ years of experience in software development or computer science.
• Advanced Python skills and familiarity with ML and data processing libraries (TensorFlow, PyTorch, Scikit-Learn, Pandas).
• Proficiency with SQL and large-scale data handling.
• Strong understanding of A/B testing and experimentation approaches.
• Knowledge of MLOps practices, including model deployment and monitoring.
• Experience with workflow orchestration tools like Airflow.
• Familiarity with processing real-time data using technologies such as Kafka, Redis.
• Fluent in Russian and English, both written and verbal.

Benefits

• Medical compensation.
• Compensation for sports activities.
• Well-being webinars and workshops.
• Wellness Day: 4th Friday off monthly.
• Remote work.
• 21 working days of vacation.
• 5 personal days per year.
• Language learning bonus €150 per month.
• 80% paid professional employee training.
• Provided tech equipment.