Join Burny Games — a Ukrainian company that creates mobile puzzle games. Our mission: to challenge players’ minds every day with innovative, high-quality gaming experiences. What makes us proud? * In just two years, we’ve launched two successful mobile games worldwide: Playdoku and Colorwood Sort. We have paused some projects to focus on making our games better and helping our team improve. * Our games have been enjoyed by over 8 million players worldwide, and we keep attracting more players. * We’ve created a culture where we make decisions based on data, which helps us grow every month. * We believe in keeping things simple, focusing on creativity, and always searching for new and effective solutions.
What are you working on? * Genres: Puzzle, Casual * Platforms: Mobile, iOS, Android, Social
Top Titles: Colorwood Sort — #1 sorting game Colorwood Words — made in 71 days Colorwood Blocks — unique art & gameplay Playdoku — our first top game Team size and structure? 100+ employees
Our ideal candidate should have: * 7+ years of machine learning experience with at least 2 years building recommender systems or reinforcement learning solutions. * Strong theoretical and practical knowledge of one of contextual bandits, exploration-exploitation trade-offs, causal inference, and sequence modeling is mandatory. * Proven ability to architect, develop, and deploy production-scale ML systems, preferably within gaming or digital products. * Proficient in Python and ML frameworks like TensorFlow or PyTorch, with strong software engineering discipline. * Experience with cloud infrastructure (preferably GCP), containerization (Docker/Kubernetes), and scalable data pipelines. * Familiarity with online learning systems, real-time inference, and low-latency model deployment * Excellent communication skills to clearly convey complex ML concepts to technical and non-technical stakeholders. * Proactive, entrepreneurial mindset, comfortable owning and driving an ML track end-to-end.
Will Be a Plus * Experience with Bayesian bandits or causal reinforcement learning. * Familiarity with big data technologies. * Prior exposure to game development. * Contributions to open source or academic research in bandits or recommender systems. * Understanding or experience with ML-Ops practices.
Key Responsibilities: * Lead the design and development of fine-grained player segmentation and personalization systems [also known as microsegmentation]. * Architect and build the end-to-end ML pipelines owning this track from the ground up. * Collaborate cross-functionally with product, engineering, and analytics teams to embed ML-driven personalization into live games, improving retention, ARPU, and engagement. * Stay at the forefront of research in contextual bandits, reinforcement learning, causal ML, and recommender systems, translating innovations into practical solutions.
What we offer: * 100% payment of vacations and sick leave [20 days vacation, 22 days sick leave], medical insurance. * A team of the best professionals in the games industry. * Flexible schedule [start of work from 8 to 11, 8 hours/day]. * L&D center with courses. * Self-learning library, access to paid courses. * We provide the necessary hardware for work.
The recruitment process:
CV review → Interview with Talent Acquisition Manager → Interview with Head of Analytics → Interview with CPO & CEO → Job offer.
If you share our goals and values and are eager to join a team of dedicated professionals, we invite you to take the next step.
