Senior Data Scientist - AI Foundations, ML Bots

Riot Games • Los Angeles, CA

6h

About The Position

On AI Foundations, our mission is to unlock cutting edge player experiences through the power of ML and AI technologies. Within this space, the ML Bots team partners with teams across Riot to accelerate the development and deployment of new machine learning & AI systems. We dive into diverse, high impact projects across Riot, and help take them from ideas to fully fledged features.
As a Senior Data Scientist specializing in applied machine learning, you will design and deliver Game Understanding Agents. This includes building and deploying in-game Game AI capabilities that enhance both the player and developer experience. You will apply methods in reinforcement learning, imitation learning, and simulation-based training for game AI, working closely with engineers on the ML Bots team to bring models from research into production. In addition to delivering high-quality systems, you will contribute to the team’s technical practices by sharing expertise, supporting experimentation, and mentoring junior teammates. By combining modern ML approaches with knowledge of game mechanics, you will help create autonomous agents that can play, understand, and adapt like real players.

Requirements

• Bachelor’s degree or higher in computer science, statistics, applied mathematics, or a related quantitative field, or equivalent practical experience.
• 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; or if from academia, a MS/Ph.D. in a related field with relevant applied experience.
• 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.
• Collaboration experience with cross-disciplinary teams, including game engineers and designers.
• 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).

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.

Benefits

• Riot focuses on work/life balance, shown by our open paid time off policy and other perks such as flexible work schedules.
• We offer medical, dental, and life insurance, parental leave for you, your spouse/domestic partner, and children, and a 401k with company match.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 1,001-5,000 employees