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## About the role
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.
## 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
- 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.
## Nice to have
- 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.
## What we offer
- Competitive salary and equity package
- Comprehensive health, dental, and vision benefits
- 401(k) matching
- Flexible work arrangements
- Professional development opportunities
- Collaborative and innovative work environment
## About us
We are a leading technology company dedicated to advancing the future of computing. Our mission is to build the next generation of hardware and software solutions that empower organizations to solve the world's most complex challenges. Join us in shaping the future of AI, high-performance computing, and datacenter infrastructure.
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