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.
