ML Engineer

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.