Hardware Health
Overview
Microsoft AI operates one of the world’s most advanced AI training infrastructures, featuring multi-gigawatt clusters spanning tens of thousands of high-performance GPUs, ultra-low-latency NVLink/NVSwitch networks, and innovative liquid-cooling systems. Our team is seeking a Member of Technical Staff - Hardware Health, to ensure these systems deliver sustained reliability, performance, and availability across exascale-class deployments.
We work closely with research, hardware, datacenter, and platform engineering teams to develop predictive health models, failure detection frameworks, and autonomous remediation systems that keep our AI clusters operating at frontier scale.
Our newly formed organization, Microsoft AI, is dedicated to advancing Copilot and other consumer AI products and research. The team is responsible for Copilot, Bing, Edge, and generative AI research. Join us and help shape the future of personal computing.
Responsibilities
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Design and develop next-generation hardware health monitoring and diagnostic frameworks for large GPU clusters (NVL16/NVL72/GB200+ scale).
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Build predictive analytics pipelines leveraging telemetry, power, and thermal data to anticipate hardware degradation and systemic issues.
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Collaborate with silicon, firmware, and datacenter engineers to identify root causes and remediate large-scale hardware anomalies.
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Define system health KPIs (e.g., NIS/RIS, MTBF, failure domain analysis) and integrate them into real-time observability platforms.
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Lead incident triage for high-impact GPU, network, and cooling issues across distributed clusters.
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Drive automation in health management to reduce manual intervention to the top 5% of anomalies.
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Partner with cross-functional teams to influence hardware design for reliability, thermal efficiency, and serviceability.
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Embody our Culture and Values.
Qualifications
- Bachelor's Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python
- OR equivalent experience.
- Master's Degree in Computer Science or related technical field AND 8+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python
- OR Bachelor's Degree in Computer Science or related technical field AND 12+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python
- OR equivalent experience.
- Experience working with large-scale HPC or GPU systems (NVIDIA H100/GB200 or equivalent).
- Deep understanding of GPU architecture, high-speed interconnects (NVLink, InfiniBand, RoCE), and large datacenter topologies.
- Proficiency in hardware telemetry, diagnostics, or failure analysis tools.
- Experience with exascale-class systems or cloud-scale AI clusters.
- Familiarity with reliability modeling, machine learning-based anomaly detection, or predictive maintenance.
- Contributions to large-scale infrastructure operations, supercomputing centers, or AI hardware design.
Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
https://careers.microsoft.com/us/en/us-corporate-pay
This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.
Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.
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