TL;DR

Staff Data Scientist (AI): Lead the design and development of Game Understanding Agents with an accent on reinforcement learning, imitation learning, and simulation-based training for game AI. Focus on creating autonomous agents that can play, understand, and adapt like real players.

Location: Los Angeles, USA

Salary: $209,900.00 - $293,400.00 USD + incentive compensation + equity + 401K with company match + medical, dental, vision, and life insurance + short and long-term disability + open PTO

Company

Riot focuses on creating games and experiences that make it better to be a player.

What you will do

Lead the design and implementation of ML systems using methods including reinforcement learning and imitation learning.
Lead the development, and deployment of 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.
Create reusable training and evaluation pipelines that can be applied across multiple game genres.
Develop predictive features and signals from gameplay telemetry, unstructured game data, and simulation outputs.
Collaborate with game and platform engineers, along with UX teams, to ensure the operational reliability of autonomous agents operating in live player environments.
Mentor junior and senior-level ML engineers, elevating expertise in advanced ML methods for game AI and guiding architectural and system-level decisions.

Requirements

Extensive experience (5+ years) delivering ML systems in production, including reinforcement learning, imitation learning, or simulation-based training in rich, interactive environments. Or if from academia, Ph.D. in a related field, with 3+ years experience.
Experience developing predictive features and signals from gameplay telemetry, simulation data, or other complex interactive environments.
Strong track record building and optimizing agent-based systems or world models for dynamic, player-facing environments.
Experience with relevant ML methods, including reinforcement learning and imitation learning.
Experience with experiment design, model evaluation, and optimization for autonomous agents.
Proficiency in Python and experience working with modern ML/data science libraries and frameworks (e.g. PyTorch/TensorFlow, pandas).

Culture & Benefits

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.
401k with company match.