Staff Machine Learning Engineer - Game Tech Group, ML Platform

Sourced from newjob.tech

Riot Games is hiring a Staff Machine Learning Engineer to build and scale the ML Platform powering AI and ML systems across game development, player experiences, and internal tools. You will architect model deployment, observability, and lifecycle management systems while shaping the long-term direction of Riot's ML platform. The role applies modern MLOps practices to improve reliability, scalability, and developer experience for teams building AI-powered products.

• Design and operate AI & ML inference infrastructure, including deployment pipelines and CPU/GPU-aware orchestration
• Develop CI/CD workflows enabling rapid iteration and safe promotion to production
• Optimize infrastructure for varied model architectures, from foundation models to gradient boosted trees, for throughput, latency, and availability
• Establish ML deployment best practices such as 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 technical direction across Riot's ML ecosystem
• Collaborate with researchers and game teams to build reusable platform capabilities

• 6+ years of engineering experience, with time on ML/AI, platform, or infrastructure teams
• Experience operating inference platforms such as KServe and production ML infrastructure including Feast, Milvus, or similar
• Experience with inference serving frameworks such as NVIDIA Triton/Dynamo, TorchServe, or similar
• 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 in real-time or latency-sensitive environments
• Hands-on optimization of ML & AI deployments (LLMs, diffusion models) 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