Staff Data Scientist – VALORANT, Deep Learning

Position Overview

Riot Data Scientists combine their broad technical expertise across data processing, automation, machine learning ("ML"), artificial intelligence ("AI"), and experimental design to inform decisions and develop data-powered products. As a Senior Data Scientist, you'll dive into projects across all areas of game development and will directly impact Riot's live games. As a Data Scientist on the Valorant Data Ops team, you will answer the question "How can data help us deliver the best possible player experience?" You will use pre-production datasets and simulations to help designers answer their most nuanced game questions, build production quality ML models for skill estimation, game understanding, matchmaking, personalization, and more, and collaborate with producers, game designers, analysts, and engineers – both on game teams directly and in partnership with shared platform teams. You will report directly to the Data Science Manager within Valorant Studio. For this role, success comes through craft expertise, a collaborative spirit, and decision-making that prioritizes the delight of players.

Key Responsibilities

• Lead the modeling strategy for deep learning production quality ML models
• Develop predictive features and signals from gameplay telemetry, unstructured game data, and simulation outputs, ensuring quality, interpretability, and reliability
• Design and implement ML systems using methods including reinforcement learning and imitation learning
• Define evaluation frameworks for game AI that balance generalizable approaches with genre-specific metrics
• Mentor senior and staff-level ML engineers in advanced ML for game AI and architectural decision-making
• Collaborate with game and platform engineers, along with UX teams, to integrate models into production systems to enhance player experience and maintain operational reliability
• Represent the deep learning team and contribute to shared frameworks

Required Qualifications

• Extensive experience (4+ years) delivering ML systems in production, including reinforcement learning, imitation learning, or simulation-based training in rich, interactive environments
• Proven ability to design modeling strategies and architectures
• Expertise in developing predictive features and signals from gameplay telemetry, simulation data, or other complex interactive environments
• Strong track record building deep learning systems for dynamic, player-facing environments
• Hands-on experience with relevant ML methods including reinforcement learning and imitation learning
• Mastery of experiment design, model evaluation, and optimization for deep learning
• Track record of incorporating human considerations into AI applications, such as responsible AI practices and human-computer interaction or UX best practices
• Experience mentoring engineers and collaborating with cross-disciplinary teams
• Familiarity with integrating deep learning models in live game environments with game and platform engineers

Benefits & Perks

Riot focuses on work/life balance with an open paid time off policy, flexible work schedules, comprehensive medical, dental, and life insurance, parental leave for you and your family, and a 401k with company match.