Staff Data Scientist - AI Foundations, ML Bots

Posted 13 Days Ago
2 Locations
In-Office
Senior level
eCommerce • Gaming
Riot Games is committed to changing the way video games are developed, published, and supported for players.
The Role
The Staff Data Scientist will lead the design and development of Game Understanding Agents using machine learning methods, mentoring engineers and setting technical direction.
Summary Generated by Built In

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 Staff Data Scientist specializing in applied machine learning, you will lead the design and development of Game Understanding Agents.  This includes deployment of in-game Game AI capabilities that enhance both the player and developer experience. You will advance methods in reinforcement learning, imitation learning, and simulation-based training for game AI, guiding engineers on the ML Bots team in building and scaling production-ready systems. In addition to delivering high-quality systems, you will shape technical direction within the team by setting standards for experimentation, reviewing designs, and mentoring peers across disciplines. By combining modern ML approaches with deep knowledge of game mechanics, you will lead the creation of autonomous agents that can play, understand, and adapt like real players. In doing so, you will help establish Riot’s applied ML practices in game AI and accelerate their impact across multiple projects.

Responsibilities:
  • Lead the design and implementation of 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.
  • 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.
  • You will create reusable training and evaluation pipelines that can be applied across multiple game genres while adapting to the unique constraints of each title.
  • 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 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. 
  • Contribute to and shape shared frameworks for autonomous agent development, accelerating adoption of best practices across Riot.
Required Qualifications:
  • Extensive experience (5+ years) delivering ML systems in production, including reinforcement learning, imitation learning, or simulation-based training in rich, interactive environments such as game worlds or multi-agent simulations; 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 (such as behavior cloning and 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.
  • Experience with experiment design, model evaluation, and optimization for autonomous agents.
  • 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 ML-driven agents into live game environments with game and platform engineers.
  • Familiarity with MOBA game mechanics and their implications for agent design and evaluation. 
  • Proficiency in Python and experience working with modern ML/data science libraries and frameworks (e.g. PyTorch/TensorFlow, pandas).

For this role, you'll find success through craft expertise and a collaborative spirit that prioritizes the delight of players. We will look at your past studies and experience, but for this role, we also look for dedicated people with a personal relationship with games. If you embody player empathy and care about players' experiences, this is the role for you!


Our Perks:

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. Check out our benefits pages for more information.

At Riot Games, we put players first. That mission drives every decision in our quest to create games and experiences that make it better to be a player. Whether you’re working directly on a new player-facing experience or you’re supporting the company as a whole, everyone at Riot is part of our mission. And just like in our games, we’re better when we work together. Our goal is to create collaborative teams where you are empowered to bring your unique perspective everyday. If that sounds like the kind of place you want to work, we’re looking forward to your application.


It’s our policy to provide equal employment opportunity for all applicants and members of Riot Games, Inc. Riot Games makes reasonable accommodations for handicapped and disabled Rioters and does not unlawfully discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, handicap, veteran status, marital status, criminal history, or any other category protected by applicable federal and state law. We consider for employment all qualified applicants, including those with criminal histories, in a manner consistent with applicable federal, state and local law, including the California Fair Chance Act, the City of Los Angeles Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, the San Francisco Fair Chance Ordinance, and the Washington Fair Chance Act.

Per the Los Angeles County Fair Chance Ordinance, the following core duties may create a basis for disqualifying candidates with relevant criminal histories:

  • Safeguarding confidential and sensitive Company data
  • Communication with others, including Rioters and third parties such as vendors, and/or players, including minors
  • Accessing Company assets, secure digital systems, and networks
  • Ensuring a safe interactive environment for players and other Rioters

These duties are directly related to essential operations, safety, trust, and compliance obligations within our organization. Please note that job duties may evolve based on business needs and additional responsibilities may be assigned as necessary to maintain operational efficiency and security. 

Top Skills

Python
PyTorch
TensorFlow
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The Company
4,500 Employees
Year Founded: 2006

What We Do

Since 2006, Riot Games has stayed committed to changing the way video games are developed, published, and supported for players. From our first title, League of Legends, to 2020’s VALORANT; we have strived to evolve the community with growth in Esports, and expansion from games into entertainment. Players are the foundation of Riot's community and because of them, we’re able to reach new heights.

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