About the company
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.
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
Requirements
- 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
Conditions
- Open paid time off policy
- Flexible work schedules
- Medical, dental, and life insurance
- Parental leave
- 401k with company match