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Staff Engineer - Platform Bring-up and Validation

Austin, Texas, United States

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 set 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 principled and dynamic Lead Systems and Validation Engineer to drive end-to-end system validation for AI compute blade and rack platforms. This high-visibility role focuses on first silicon bring-up, system enablement, and post-silicon validation across hardware, firmware, and software domains. You will lead validation strategy, execution, and debug while collaborating closely with cross-functional engineering teams to deliver high-quality, industry-leading AI systems.

The Team

The Systems Validation team is responsible for enabling and validating Graphcore’s AI compute platforms from first silicon through production. The team works closely with system architects, firmware, silicon, and infrastructure teams to ensure system readiness, scalability, and quality at rack level.

Responsibilities and Duties

  • Lead system enablement including first silicon bring-up and integration of firmware and platform components to meet system architecture specifications.
  • Develop validation methodologies, lab hardware infrastructure, system software capabilities, and debug tools for blade and rack-level validation.
  • Triage and debug issues across bring-up, post-silicon validation, and production phases ensuring timely resolution with high quality.
  • Define and own validation test plans, develop test cases, and drive execution across domains such as CPU, GPU, memory, HBM, and IO.
  • Drive innovation in validation through development of tools, scripts, and improved methodologies to enhance coverage, efficiency, and quality.
  • Enable comprehensive system verification by integrating storage, networking, and infrastructure capabilities within lab environments.  
  • Collaborate with multi-functional teams including system architecture, embedded software, hardware build, and ODM partners.    
  • Provide technical leadership and mentorship, fostering engineering perfection and continuous improvement.

Candidate Profile

Essential:

  • Strong analytical and problem-solving skills with high attention to detail.
  • Extensive experience in system validation encompassing initial silicon integration and HW/FW/SW validation.  
  • Strong understanding of industry-standard interfaces such as PCIe and CXL.
  • Experience enabling storage and networking systems in lab environments for end-to-end validation.
  • Deep knowledge of ARM or x86 architectures, SoC design, memory, RAS, and power management.
  • Experience with system-level debug, operating systems, BIOS, and device drivers.
  • Strong experience with Linux, Windows, and virtualization technologies (VMware, KVM, Hyper-V).
  • Excellent communication, organization, and cross-functional collaboration skills.
  • Ability to lead multiple workstreams and deliver under tight timelines.
  • Experience in technical program management and driving validation initiatives.

Desirable:

  • Master’s or PhD in Electrical Engineering, Computer Engineering, or related field.
  • Demonstrated ability working on complex system validation and debug in data center or rack-scale environments.
  • Experience designing or validating AI/ML rack-scale systems.
  • Knowledge of hardware development best practices and industry standards.
  • Familiarity with emerging AI and data center infrastructure technologies.
  • Experience collaborating with ODM partners globally.

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