Staff Machine Learning Engineer - Game Tech Group, ML Platform
Los Angeles, USA
- Pay
- Pay not listedSimilar roles state $165K–$240K
- Work setting
- Not stated
- Employment
- Not stated
What you’ll work on
Full postingDesign and operate AI and ML inference infrastructure, including CPU/GPU-aware orchestration
Build CI/CD workflows for safe promotion from development to production
Optimize serving for varied models for throughput, latency and availability
Establish ML deployment practices such as blue/green rollouts and shadow deployments
Reduce operational complexity and simplify platform onboarding for engineers
From the employer’s posting
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
What you’ll bring
All qualificationsCore experience
- 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
Preferred experience
- 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
Qualification wording
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
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
Tools in this posting
- Terraform
Source — Tool mentions in context
- 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
Benefits in the posting
Full benefits wording- 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.
From the employer’s posting.
Posting record
Report an errorOpen 4 monthsWe first saw this posting 143 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
- Status in our records
- Live
- First seen by us
- Jun 6, 2026 · 143 days ago
- Recorded sightings
- 161
- Last seen by us
- Oct 28, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Your next step
- Have your resume and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
- Ask the employer about the pay range before committing time to the process.
Complete your application on www.riotgames.com. The employer’s form will show what is required.
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Job description
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.
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- Location & working pattern
Los Angeles, USA
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