Skip to content
Level

Riot Games

Staff Machine Learning Engineer - Game Tech Group, ML Platform

Riot Games is hiring a Staff Machine Learning Engineer - Game Tech Group, ML Platform 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 Milvus, Python and Kubernetes among its tools and skills.
  • Level classes it as a senior role.
  • Riot Games has 183 other open roles on Level.

AI in this role

Design, scale, and operate machine learning infrastructure and inference pipelines to support AI systems across Riot Games.

milvuspythonkubernetesdockerci-cd
ai-agentsml-opsmlopsmodel-servingorchestrationinfrastructuredistributed-systems

Riot engineers bring deep knowledge of specific technical areas but also value the opportunity to work in many broader domains. As a Staff Machine Learning Engineer at Riot, you’ll also dive into projects that focus on team cohesiveness and cross-team goals. You’ll lead without authority and provide other engineers with a clear illustration of extraordinary engineering.

Riot Games is building the next generation of its ML Platform to support AI and machine learning systems across game development, player experiences, and internal tools. We’re looking for a Staff Machine Learning Engineer to help design and scale the infrastructure powering a wide range of ML workloads and evolving AI systems across Riot. The ML Platform team builds and operates the shared infrastructure behind Riot’s AI ecosystem, including model serving, orchestration, feature management, and deployment workflows. Our goal is to help teams across Riot move ML systems from experimentation into reliable production services quickly and confidently. As a Staff Machine Learning Engineer on the ML Platform team, you will architect systems for model deployment, observability, and lifecycle management while helping shape the long-term direction of Riot’s ML platform. You will apply modern MLOps practices to improve reliability, scalability, and developer experience for teams building AI-powered products across Riot. You will report to the Engineering Manager.

Responsibilities:

  • Design and operate AI & ML inference infrastructure, including deployment pipelines and CPU/GPU-aware orchestration
  • Develop CI/CD workflows that enable rapid iteration and safe promotion from development to production
  • Optimize infrastructure supporting varied model architectures, from foundation models to gradient boosted trees, for high throughput, low latency, and high availability
  • Establish and evolve ML deployment best practices, including multi-version models, blue/green rollouts, shadow deployments, and rollback strategies
  • Improve developer experience by reducing operational complexity and simplifying platform onboarding
  • Influence long-term platform architecture and help shape technical direction across Riot’s ML ecosystem
  • Collaborate with researchers and game teams to understand product needs and build reusable platform capabilities
  • Use modern AI-assisted development tools and workflows thoughtfully to accelerate iteration, while maintaining engineering quality and reliability

Required Qualifications:

  • 6+ years of experience in engineering, with time spent on ML/AI, platform or infrastructure teams
  • Experience operating inference platforms such as KServe and production ML infrastructure including Feast, Milvus, or similar open-source systems
  • Experience with one or more inference serving frameworks, including NVIDIA Triton/Dynamo, TorchServe, or similar systems
  • Familiarity with GPU orchestration, performance tuning, and cost-aware scheduling
  • Experience with CI/CD workflows, infrastructure-as-code (e.g., Terraform), and artifact management
  • Experience building and operating services within distributed or service-oriented architectures

Desired Qualifications:

  • Experience building ML infrastructure within a real-time, or latency-sensitive environment
  • Hands-on experience with optimizing ML & AI deployments (LLMs, diffusion models, etc.) for throughput, latency and reliability
  • Familiarity with agentic workflows and orchestration frameworks for LLM-based systems
  • Passion for player experience, game systems, or creative technology development

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.

How we rate this

Staff Machine Learning Engineer - Game Tech Group, ML Platform at Riot Games rates 90 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

AI agentsML OpsMLOpsModel ServingOrchestrationInfrastructureDistributed SystemsMilvus

Also common in machine learning engineer jobs at this level

Pay

Typical machine learning engineer job
$200k

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 decide when an AI agent can act on its own versus asking for approval first?
  2. How do you monitor a model once it's live, and how do you know it needs retraining?
  3. Tell me about a project where mlops was part of your work. What did you do?
  4. Tell me about a project where model serving was part of your work. What did you do?
  5. Tell me about a project where orchestration was part of your work. What did you do?

Adapt your resume

  • List these exact terms on your resume: AI agents, ML Ops, MLOps, Model Serving, and Orchestration. 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.

Want an expert to read your CV for this job?

Free. Send your CV and the role you want next. You get your review by email within 24 hours.

Get new machine learning engineer jobs (Builds AI ●●●●) by email

One email a week with the new machine learning engineer jobs (Builds AI ●●●●), each rated for how much AI is in the work. No recruiter spam, unsubscribe in one click.

Free. One email a week. Unsubscribe in one click.

Similar roles

Data roles that build AI, at other companies.

What kind of AI work fits you?

Answer 12 practical questions in about three minutes. Get a simple profile, the work it points to, and live roles to explore next.

Find my next step

More jobs at Riot Games

More machine learning engineer jobs

Related searches

Same AI level

Jobs by city