Riot Games is looking to unlock cutting edge player experiences through the power of ML and AI technologies, specifically by developing Game Understanding Agents that enhance both the player and developer experience.
Requirements
- Experience developing predictive features and signals from gameplay telemetry, simulation data, or other complex interactive environments.
- Hands-on experience building and optimizing agent-based systems or models for dynamic, player-facing environments.
- Experience designing experiments, evaluating models, and optimizing performance for autonomous agents.
- Awareness of human considerations in AI applications, such as responsible AI practices, player experience, and UX best practices.
- Familiarity with integrating ML-driven agents into live game environments.
- Proficiency in Python and experience with modern ML/data science libraries and frameworks (e.g., PyTorch or TensorFlow, pandas)
- 3+ years of experience delivering ML systems in production, including reinforcement learning, imitation learning, or simulation-based training in interactive environments such as game worlds or multi-agent simulations
Responsibilities
- Design and implement ML systems using methods including reinforcement learning and imitation learning (e.g., behavior cloning, inverse reinforcement learning), on-/off-policy algorithms, policy gradient methods, behavior shaping, and hybrid systems that combine learned policies with rule-based or scripted components.
- Develop and deploy in-game Game AI capabilities, focusing on training agents that can understand game state, make decisions, and act in ways that create compelling player experiences.
- Contribute to build adaptable training and evaluation pipelines, supported by robust tooling designed to capture the title’s specific mechanics, while evolving to meet new gameplay requirements
- Develop predictive features and signals from gameplay telemetry, unstructured game data, and simulation outputs, ensuring quality, interpretability, and reliability.
- Collaborate with game and platform engineers, along with UX teams, to integrate autonomous agents into live player environments with high reliability.
- Mentor junior team members in applied ML methods and best practices for production AI systems.
- Contribute to shared frameworks and tools for autonomous agent development, improving efficiency and maintainability.
Other
- Bachelor’s degree or higher in computer science, statistics, applied mathematics, or a related quantitative field, or equivalent practical experience.
- Collaboration experience with cross-disciplinary teams, including game engineers and designers.
- Player empathy and care about players' experiences
- Open paid time off policy and other perks such as flexible work schedules
- Medical, dental, and life insurance, parental leave for you, your spouse/domestic partner, and children, and a 401k with company match
