Burny Games
Опис
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
[https://apps.apple.com/de/app/playdoku-puzzle-blockspiel/id6443701534] and
Colorwood Sort
[https://apps.apple.com/us/app/colorwood-sort-puzzle-game/id6475673897].
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.
🔥 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
[https://apps.apple.com/de/app/playdoku-puzzle-blockspiel/id6443701534] and
Colorwood Sort
[https://apps.apple.com/us/app/colorwood-sort-puzzle-game/id6475673897].
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.