About the company
Roblox is building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device.
Responsibilities
- Drive strategy and roadmap for Compute Platform spanning Managed Kubernetes (Roblox Kubernetes Service), Managed Compute Services and other critical distributed systems, and our fleet of GPU and CPU machines managed via unified Fleet APIs - all across on-prem and cloud.
- Drive the evolution of our Compute infrastructure to support Roblox’s most critical workloads - from AI to Storage to Data Analytics and more - each with their own distinct requirements.
- Build and scale our GPU infrastructure to support training and inference for frontier models, enabling innovation at scale while optimizing cost-to-serve.
- Stay laser-focused on Compute Platform Reliability for AI and other Roblox workloads, lowering mean-time-to-detection and recovery from failures.
- Partner closely with seven key platform teams to understand their use cases and empower them with Compute Platform primitives enabling them to build on top easily.
- Lead cross-functionally, acting as the connective tissue between Compute Platform Users, Engineers, AI researchers, Product, Finance, and Roblox leadership.
Requirements
- 7+ years of product management experience, focused on Compute infrastructure or distributed systems at scale.
- Deep practical understanding of Kubernetes internals and control plane components (API Server bottlenecks, Etcd scaling limitations, Kubelet behavior, etc) and experience productizing custom Kubernetes Operators, Controllers, and Custom Resource Definitions (CRDs) to extend platform capabilities beyond vanilla implementations.
- Deep familiarity with GPU/accelerator architecture and scheduling challenges, including topology-aware placement, preemption, hardware affinity constraints, and mechanisms to validate resource readiness before scheduling to avoid wasted compute cycles.
- Familiarity with cloud-native service networking including microservices, CNIs, and enterprise-grade service mesh architectures.
- Built production-grade compute platforms where efficiency, reliability, and developer experience were designed-in from day one.
- The ability to balance the needs of multiple users and stakeholders and make optimal tradeoffs between utilization, latency, cost and time-to-ship while maintaining reliability.
- A builder mindset - you are passionate about prototyping, evolving products through rapid iteration, and leveraging AI for ideation and unlocking value for users.
- Preferred: Experience building Compute infrastructure on AWS, Google Cloud Platform (GCP), Azure or other cloud providers; Background in AI model development, training, inference; Kernel-level experience or familiarity with custom kernel drivers; Experience building agentic systems for Compute or infrastructure.
Conditions
- Annual Salary Range: $280,540 — $330,950 USD
- Roles that are based in an office are onsite Tuesday, Wednesday, and Thursday, with optional presence on Monday and Friday