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Gameplay/AI Engineer

gameboost
Companygameboost
CategoryEngineering
Location
Remote
EmploymentNot stated
LevelNot stated
SalaryNot stated by the employer
Posted12 Dec 2025
Last verified3 Aug 2026
SourceEmployer career page (teamtailor)
Applications are handled by the employer, not by us.Apply on the employer's site →
Description
Gameplay/AI Engineer Do you want to shape the future of gameplay AI and build systems that players can feel, not just see? We are looking for a creative and technically strong Gameplay AI Engineer who wants to work at the intersection of gameplay, AI systems, and reinforcement learning , helping push emergent and expressive gameplay forward. You will work closely with designers, gameplay engineers, and stakeholders to prototype, build, and evolve AI behaviors and learning-driven systems aligned with our technical roadmap. What you will do Improve and maintain low-level gameplay AI systems aligned with the technical roadmap Design and develop AI systems in close collaboration with game design Prototype, experiment, and build AI behaviors for gameplay scenarios Work closely with stakeholders and game teams to prototype new RL-based locomotion and gameplay platforms Research, develop, and train reinforcement learning models Analyze model performance and provide clear visualizations and insights Improve game-side training frameworks to make models easier to train, debug, and iterate on Identify opportunities to apply new AI and ML technology to enable more emergent gameplay Stay up to date with current research and share knowledge within the team We would love if you have A creative and curious mindset A strong background in C++ Solid experience with gameplay engineering A good grasp of what good gameplay looks and feels like The ability to “speak design” and collaborate effectively with designers Experience working in Unreal Engine An interest in computer science and programming as a craft Professional English communication skills Bonus points if you have experience with Multiplayer systems Shooter or third-person games Designing reward functions for reinforcement learning Training curriculums for ML models Implementing and evaluating machine learning methods Reinforcement learning–specific optimization algorithms Python programming for tooling, training, or analysis
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