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Riot Games

Senior Manager, Machine Learning Engineering - League of Legends

Riot Games is hiring a Senior Manager, Machine Learning Engineering - League of Legends in Los Angeles, United States. Level rates it ; you can apply on Riot Games.

Level's read on this job

  • Builds AI ●●●● is how Level rates this machine learning engineer role: the job is building AI systems.
  • The posting mentions MLOps and AI safety among its tools and skills.
  • Level classes it as a senior role.
  • Riot Games has 184 other open roles on Level.
  • Posted in the last few days.

AI in this role

ml-opsai-safety

As a Senior Manager, ML Engineering, you will lead the Machine Learning Engineering team responsible for building and operating machine learning systems that power League of Legends. This team delivers both player-facing ML experiences and developer-facing ML tools, enabling in-game and around-game capabilities such as recommendations, player behavior modeling, matchmaking, and experimentation-driven personalization. 

In this role, you will be accountable for the technical vision, execution, and business impact of ML applications in League of Legends. You will shape the end-to-end ML engineering strategy, from data and feature pipelines to model development, deployment, evaluation, and operations, ensuring systems are scalable, reliable, and measurable in production. You will partner with development themes’ product and production leaders to enable the development of League of Legends existing and future player experiences. 

You will report to the Data Engineering Director of League Insights. This role is based out of our Los Angeles Headquarters.

Responsibilities

  • Manage a team of highly skilled engineers, driving performance, developing future leaders, identifying growth opportunities, and ensuring strong delivery and outcomes.
  • Define, own, and socialize an engineering vision for the organization, working with cross-functional and engineering leaders to create a long-term organizational and staffing plan aligned with technical and product goals.
  • Contribute to all parts of team leadership, including budgeting, recruiting, hiring, mentoring, performance management, and managing contingent staff.
  • Set direction for MLOps efforts across the ML product lifecycle, continuously improving model quality, efficiency, reliability, and operational excellence.
  • Collaborate closely with cross-functional partners across LoL PC, including product management and technical production, to deliver scalable, reliable, and high-impact ML-powered solutions.
  • Foster effective communication and collaboration within engineering teams, central MLE groups, and across other LoL PC departments.
  • Build stronger cross-Riot MLE craft support and contribute towards ongoing improvements to craft standards.
  • Stay current with industry trends and emerging technologies in applied ML and MLOps, guiding pragmatic adoption of best practices that improve product quality and player impact.
  • Continue to hone your individual skills so you can deliver projects in a Player-Coach dynamic.

Required Qualifications

  • Bachelor’s degree in Computer Science or a related field, or equivalent experience.
  • 10+ years of experience building and operating large-scale software systems, with significant experience in production ML systems.
  • Strong expertise in computer science fundamentals, including system design, data structures, and algorithms.
  • Experience with Java, C++, Python, or similar languages in large-scale, production environments.
  • Deep knowledge of MLOps best practices, including model lifecycle management, experimentation, monitoring, and deployment at scale.
  • Experience collaborating across multiple teams, departments, and disciplines to create solutions.
  • Experience with project planning, prioritization frameworks, and guiding investment strategies across people, platforms, and systems.

Desired Qualifications

  • Master’s degree in Computer Science or a related field, or equivalent experience.
  • Familiarity with Responsible AI frameworks, fairness considerations, and long-term player impact measurement.
  • Experience with large-scale experimentation platforms and online evaluation frameworks.
  • Experience leading full-stack teams.
  • Experience leading distributed or remote teams.

For this role, you will find success through craft expertise, a collaborative spirit, and decision-making that prioritizes the delight of players. We will be looking at your past studies, experience, and your personal relationship with games. If you embody player empathy and care about players' experiences, this could be your role!

 

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. 

How we rate this

Senior Manager, Machine Learning Engineering - League of Legends at Riot Games rates 88 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

ML OpsAI Safety

Also common in machine learning engineer jobs at this level

Pay

Typical machine learning engineer job
$199k

This posting doesn't list pay. Use the typical machine learning engineer figure when pay comes up. See machine learning engineer jobs

Questions you could be asked

  1. How do you monitor a model once it's live, and how do you know it needs retraining?
  2. How do you think about the risk of an AI system in this kind of role failing silently?
  3. How would you decide a model or AI system is ready to ship?
  4. Tell me about a time a model underperformed in production. How did you find out, and what did you change?

Adapt your resume

  • List these exact terms on your resume: ML Ops and AI Safety. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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