Hardware Health

Microsoft AI•Redmond, WA

9d•$119,800 - $304,200•Onsite

About The Position

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. Our mission is to build AI that amplifies human potential and empowers people around the world. We strive to deliver breakthroughs that advance science, education, productivity, and global well-being. We’re also fortunate to partner with incredible product teams giving our models the chance to reach billions of users and create immense positive impact. If you’re a brilliant, highly-ambitious and low ego individual, you’ll fit right in—come and join us as we work on our next generation of models! MAI employees are expected to work from a designated Microsoft office at least four days a week if they live within 50 miles (U.S.) or 25 miles (non-U.S., country-specific) of that location. This expectation is subject to local law and may vary by jurisdiction.

Requirements

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.

Nice To Haves

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.

Responsibilities

Design and develop next-generation hardware health monitoring and diagnostic frameworks for large GPU clusters (NVL16/NVL72/GB200+ scale).
Build predictive analytics pipelines leveraging telemetry, power, and thermal data to anticipate hardware degradation and systemic issues.
Collaborate with silicon, firmware, and datacenter engineers to identify root causes and remediate large-scale hardware anomalies.
Define system health KPIs (e.g., NIS/RIS, MTBF, failure domain analysis) and integrate them into real-time observability platforms.
Lead incident triage for high-impact GPU, network, and cooling issues across distributed clusters.
Drive automation in health management to reduce manual intervention to the top 5% of anomalies.
Partner with cross-functional teams to influence hardware design for reliability, thermal efficiency, and serviceability.
Embody our Culture and Values.