Description

What You'll Do

You will work with our team of applied research engineers at the intersection of computer vision, gameplay agents, natural language processing, and machine learning to create state-of-the-art tools to support game developers in our ecosystem. The focus will be on bots (trained gameplay agents, intelligent NPCs, companions, world modeling), as well as automation of key areas (including moderation, security, and QA testing). You will be responsible for the design, implementation, and deployment of production-ready machine learning models that can be integrated into our ecosystem.

Create and deliver production-ready, scalable and high-quality machine learning models and associated algorithms that can make actions in game environments.
Critically assess the effectiveness of such models and make recommendations for the ongoing roadmap.
Methodically understand and assess the effectiveness of new data channels and support collection/creation of new ones.

What We're Looking For

PhD in Computer Science, Mathematics or related field, or 3+ years of relevant industry experience.
Experience creating / applying machine learning algorithms for action modeling of bots behavior, vision-based or language-instructed, and deploying them as production-level systems in-game.
Expert, hands-on knowledge of:
- Deep learning, including but not limited to applications in the gaming industry.
- Foundational models and vision and/or language, especially vision-language-action models, reinforcement learning agents, including local deployment and model post-training of open weights models.
- Reinforcement learning, including experience with agentic systems, reward design, policy optimisation, evaluation, and building scalable training environments for agents.
- Python and associated ML tools/frameworks (numpy, scipy, sklearn, pytorch).
Experience with working collaboratively with other developers, following a flexible/agile/lean approach.