Startups · AI

Graduate Performance Engineer

Graphcore · Austin, Texas, United States · On-site

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About Graphcore

Graphcore has built a new type of processor for machine intelligence to accelerate machine learning and AI applications for a world of intelligent machines. Backed by Air Street.

About the role

As a Graduate Performance Engineer, you will contribute to the design, integration, bring-up, and validation of complex server- and rack-level performance of elaborate, large-scale systems. You will work alongside experienced engineers, software developer, and cross-functional partners while building practical skills in component, system and scale up/out performance optimization and design.

What they're looking for

  • Software and hardware architecture especially focused on performance implications
  • Familiarity with high-speed interfaces such as PCI Express (PCIe), DDR memory, or Ethernet
More about this role

Graphcore is a global leader in artificial intelligence computing systems. We design advanced semiconductors and data center hardware that deliver the specialized processing power needed to advance AI while improving the efficiency required for broad adoption.

As part of SoftBank Group, Graphcore belongs to a family of companies developing some of the world’s most transformative technologies. Our new AI Engineering Campus in Austin will play a central role in building the future of AI computing.

As a Graduate Performance Engineer, you will contribute to the design, integration, bring-up, and validation of complex server- and rack-level performance of elaborate, large-scale systems. You will work alongside experienced engineers, software developer, and cross-functional partners while building practical skills in component, system and scale up/out performance optimization and design.

Start: September, 2027

  • Support the design, peer review, bring-up, and debug of complex server- and rack-level systems.
  • Assist with modeling, design and evaluation of the complete software and hardware stack identifying performance bottlenecks, possible solutions and testing those outcomes.

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Read the full posting on Graphcore's site ↗

Performance

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