Video Games, Entertainment, Esports

Staff Machine Learning Engineer - Unpublished R&D Product

Los Angeles, CAOnsiteFull TimePosted 29 days agoVisa sponsorship available

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Required skills

Machine Learning
Reinforcement Learning
PyTorch
TensorFlow
pandas
Python
real-time
interactive environments
interacting models
feedback loops

Nice to have

multi-agent reinforcement learning
developer tooling
framework-level UI systems
infrastructure
MLOps
ML cloud services

Role summary

Riot Games is seeking a Staff Machine Learning Engineer for an unpublished R&D game project. This role involves owning the strategy, design, and implementation of ML capabilities, with a focus on enabling great player experiences. You will collaborate with developers, designers, and data scientists, applying ML/RL techniques pragmatically to product challenges. Responsibilities include refining modeling strategies, establishing pipeline architectures, driving ML/RL system applications, and defining production reliability and evaluation practices. The ideal candidate has 6+ years of experience delivering ML systems in production, including 3+ years in applied modeling or ML research, with proficiency in Python and ML frameworks like PyTorch or TensorFlow. Experience with reinforcement learning and production environments with interacting models is crucial. Desired qualifications include experience with multi-agent RL, MLOps, and game engines.

As a Staff Machine Learning Engineer on an unpublished R&D game project, you will own the strategy, design, and implementation of ML capabilities. You will work closely with developers, designers, and data scientists to understand their needs, and will be hands-on in conceptualizing, planning, implementing, and maintaining ML-driven solutions. We’re looking for someone who is passionate about enabling great player experiences, thrives in cross-disciplinary collaboration, stays current on the latest ML techniques, and can apply them pragmatically to challenging product problems. You will report to the Engineering Manager within the R&D game project.

Responsibilities:

Work closely with developers, designers, and data scientists to identify and define improvement opportunities

Refine modeling and feature strategy for using techniques such as reinforcement learning

Establish pipeline architecture patterns in partnership with central teams; build reusable training and evaluation pipelines that can be adapted to Riot-wide use cases

Drive the application of ML/RL systems to improve decision-making and adaptation

Establish research-to-production practices; balance cutting-edge techniques with production reliability

Establish evaluation practices in partnership with data scientists and analytics partners; guide experiment design for measuring model impact and set technical evaluation standards

Define reliability standards in partnership with design and engineering

Advance and strengthen engineering best practices, including code quality, automated testing, and maintainable architecture

Mentor engineers and partner disciplines through documentation, reviews, and technical design guidance

Identify technical risks and bottlenecks, proposing pragmatic solutions to keep projects moving forward

Required Qualifications:

6+ years of experience delivering ML systems in production, including 3+ years in applied modeling or ML research roles, ideally within real-time or interactive environments

Experience with reinforcement learning, including applying RL to practical production problems

Experience in production environments with interacting models, feedback loops, or systems where model behavior has downstream consequences beyond a single prediction

Proficiency with modern ML/data science libraries and frameworks such as PyTorch, TensorFlow, pandas, etc.

Experience collaborating regularly with teammates across multiple disciplines

Strong communication skills across technical and non-technical audiences

B.S. in Computer Science or equivalent experience

Proficiency in Python or similar programming languages

Desired Qualifications:

Experience with multi-agent reinforcement learning

Experience in developer tooling

Experience implementing framework-level UI systems

Experience in infrastructure and MLOps, such as ML cloud services, containers, and model telemetry

Experience working in a AAA game engine (e.g. Unity, Unreal)

Proficiency in C++

For this role, you'll 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.

Sample Riot Games interview questions

1
Create a real-time data feed for stock prices.
system designmedium
2
Buildings with an Ocean View Find all buildings that have an ocean view. Input: heights = [1,2,3,4] Output: [3] Explanation: Since the ocean is to the right, only the rightmost tallest building (index 3) is not blocked by any others.
codingmedium
3
Find the majority element in an array. Given an array of size n, find the majority element. The majority element is the element that appears more than ⌊n / 2⌋ times. You may assume that the majority element always exists in the array. Input: nums = [3, 2, 3] Output: 3 Explanation: The number 3 appears 2 times, which is strictly greater than n/2 (1.5).
codingmedium
4
Dot Product of Two Sparse Vectors Calculate the dot product of two sparse vectors. Input: nums1 = [0,1,0,0,2], nums2 = [0,0,0,0,5] Output: 10 Explanation: Multiplies the aligned non-zero values (2 * 5) and ignores all the zeros, yielding a dot product of 10.
codingmedium
5
Maximum Subarray Sum Find the maximum subarray sum in an integer array. Input: nums = [-3,-4,-1,-2] Output: -1 Explanation: Kadane's algorithm correctly identifies that the single isolated element -1 provides the highest possible sum.
codingmedium

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