Senior Data Center Network Eng: 400G/800G & GPU Clusters

Roblox

Ashburn (VA)

On-site

USD 152,000 - 191,000

Full time

8 days ago

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Job summary

Roblox in Ashburn, VA is seeking a Data Center Network Engineer to design, deploy and operate Roblox's large-scale data center fabrics and GPU clusters that power AI training and inference.

You will coordinate builds with multiple teams, validate new technologies, and contribute to automation and telemetry to improve efficiency, reliability and visibility across the network.

This is a full-time on-site role with base pay ranges and equity described on the careers page.

Qualifications

  • 6+ years designing large-scale data center fabrics (CLOS).
  • Experience with GPU clusters or AI/ML networking.
  • Proficiency deploying and managing 400G and 800G hardware.
  • Skilled in configuring and troubleshooting large-scale BGP deployments.
  • Strong knowledge of TCP/IP, UDP, DHCP, DNS; IPv4/IPv6 hands-on.
  • Preferred: QoS, IS-IS, MPLS, RSVP-TE, DWDM, NAT, open-source hardware/software.

Responsibilities

  • Drive the design, deployment, and operations of Roblox's large-scale data center network, including networking for GPU clusters that support training and inference workloads.
  • Design, qualify, and validate new technologies and hardware for scalable solutions.
  • Coordinate data center builds and projects with multiple teams, including weekly cross-team calls.
  • Work with Network Reliability Systems, Data Center Ops, Capacity Planning, Supply Chain, and Compute/ML teams to address network challenges early.
  • Contribute to automation and telemetry that improve efficiency, reliability, and visibility.

Skills

Data center fabric design
GPU clusters / AI networking
400G/800G hardware
BGP deployment & troubleshooting
TCP/IP, UDP, DHCP, DNS; IPv4/IPv6
QoS, IS-IS, MPLS, RSVP-TE, DWDM, NAT &

Job description

Roblox in Ashburn, VA is seeking a Data Center Network Engineer to design, deploy and operate Roblox's large-scale data center fabrics and GPU clusters that power AI training and inference.

You will coordinate builds with multiple teams, validate new technologies, and contribute to automation and telemetry to improve efficiency, reliability and visibility across the network.

This is a full-time on-site role with base pay ranges and equity described on the careers page.

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