ML Engineer [Data Scientist]

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.

ML Engineer [Data Scientist]

Key Skills

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