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Host Networking For Hyperscalers Segment Sales Director in San Mateo

1 active opportunities · Updated for October 2026

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Explore current host networking for hyperscalers segment sales director jobs in San Mateo. Use filters to narrow by work mode, employment type, experience and date posted.

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Roblox
📍 San Mateo• Full-time• From $345K/yr
1mo ago

Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators. At Roblox, we’re 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. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there. A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone. As a Principal Software Engineer on the Compute team, you will be the technical anchor for Roblox's GPU and AI accelerator capabilities. This is a battle-tested GPU expert role focused on the machine management layer and above: how GPU hosts are made production-ready, kept healthy, and turned into reliable compute for the workloads that depend on them. You will own the hard problems that show up only at scale, from driver and firmware management to GPU health, reliability, and performance across a rapidly growing fleet of accelerators spanning Roblox data centers and cloud environments. You will set the technical direction for GPU compute and up-level the entire organization's GPU expertise. You will: Serve as the GPU technical leader for the Compute team, partnering across Kubernetes, Machine Bootstrap, Networking, and Cloud to drive GPU strategy end to end. Own the GPU host lifecycle above raw fleet management: driver, firmware, and CUDA stack management, GPU health and telemetry, and remediation of GPU-specific failures (XID errors, ECC, thermal, NVLink and fabric faults). Architect how GPU capacity is exposed to compute platforms, including scheduling, isolation, and integration with Ku

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