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Staff Engineer - Server Hardware Compute Blade and Rack Validation Lead
Graphcore
Austin, USA
Senior
Discovered 1 weeks ago
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Role Overview
We are seeking a senior validation lead engineer to lead at-scale rack validation efforts for next-generation AI hyperscale systems.
This role focuses on post-silicon system validation across the full lifecycle, ensuring functional, electrical, and thermal performance meets product objectives.
You will own end-to-end blade and rack validation including planning, development, execution, and debug while collaborating across firmware, systems, and hardware teams.
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About us
Graphcore is one of the world’s leading innovators in Artificial Intelligence compute. It is developing hardware, software and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry. As part of the SoftBank Group, Graphcore is a member of a best-in-class family of companies responsible for some of the world’s most transformative technologies. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone. Graphcore’s teams are drawn from a diverse group of backgrounds and bring a broad range of skills and perspectives. A melting pot of AI research specialists, silicon designers, software engineers and systems architects, Graphcore enjoys a culture of continuous learning and constant innovation.
Job Summary
We are seeking a senior validation lead engineer to lead at-scale rack validation efforts for next-generation AI hyperscale systems. This role focuses on post-silicon system validation across the full lifecycle, ensuring functional, electrical, and thermal performance meets product objectives. You will own end-to-end blade and rack validation including planning, development, execution, and debug while collaborating across firmware, systems, and hardware teams.
The Team
The Rack Validation team is responsible for ensuring system readiness and quality at scale. The team works cross-functionally with firmware, silicon, and system engineering teams to validate complex AI compute platforms.
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