| Microsoft Careers

Microsoft

Hybrid

Quick summary

Work type
Hybrid
Location
Redmond, WA
Salary
$142,800–$274,800 / yr
Posted
52 days ago

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $181k
This role $209k
$101k most similar roles pay here $293k

This role pays more than 95% of similar roles. Most pay $155,000–$207,350 — the shaded band above. At the midpoint, this role pays about $209k versus about $181k for comparable roles.

Based on 238 similar postings.

Employer

About Microsoft

Microsoft Corporation is a global technology leader producing software, hardware, and cloud services including Windows, Office 365, Azure cloud platform, Xbox gaming, and Surface devices. Industry: Software & Cloud Computing

Microsoft currently has 1103 open roles on FindRole.

Listed pay typically runs $119,800–$234,700 across 985 roles with salary data.

Most-posted roles

View all roles at Microsoft

At a glance

TL;DR · | Microsoft Careers

As a Member of Technical Staff at Microsoft AI’s Superintelligence Team, you will design and scale high-performance networks for cutting-edge AI systems like Copilot. Your daily tasks include shaping end-to-end networking architecture from link-layer to fabric-wide systems, optimizing Ethernet and InfiniBand fabrics connecting thousands of GPUs in multi-megawatt data centers, and tuning the performance of AI workloads running in production clusters. You will engineer ultra-low-latency ROCE networks, design congestion-free transport mechanisms, and collaborate with Azure and Microsoft AI teams to deploy global infrastructure. Key skills include advanced ROCE transport design, congestion control, telemetry engineering, and working with leading network designers like NVIDIA and Broadcom. This role demands expertise in networking technologies, Python scripting, and proficiency in Linux environments, pushing the boundaries of physics, silicon, and software to accelerate Microsoft’s frontier AI models.

What you'll do

  • Design and optimize ultra-low-latency ROCE networks for large-scale GPU clusters.
  • Develop congestion-free transport mechanisms and tune lossless fabrics at scale.
  • Plan fabric architecture, topology, and scaling strategies for AI training clusters.
  • Implement telemetry and observability systems for reliable network operations.
  • Collaborate with leading hardware designers to deploy novel routing techniques.

What we're looking for

  • Extensive experience with advanced ROCE transport design and congestion control.
  • Expertise in fabric architecture, topology planning, and network modeling at scale.
  • Proficient in telemetry, observability, reliability engineering, and automated troubleshooting.
  • Experience developing and tuning routing techniques for large-scale network reliability.
  • Deep collaboration skills with leading network designers and silicon/network co-design teams.
  • Hands-on experience in AI training cluster bring-up, performance benchmarking, and analysis.

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