Graduate Performance Engineer: AI Hardware & Systems

Graphcore Early Careers; Austin (TX); On-site; USD 80,000 - 120,000; Full time

Job summary

Graphcore invites graduates to join our AI engineering campus in Austin as a Graduate Performance Engineer, contributing to design, integration, bring-up and validation of complex server- and rack-level performance in large-scale systems.

You will work with hardware and software teams to identify bottlenecks, model and evaluate the full stack, and develop practical optimization strategies while growing your practical technical skills.

Qualifications

• A bachelor’s or master’s degree in electrical engineering, computer engineering, or a related discipline, completed before the role’s start date. Equivalent relevant education or practical experience will also be considered.
• Foundational knowledge of software development, hardware architecture and general understanding of performance implications.
• Hands‑on experience gained through coursework, laboratories, internships, research, student projects, or personal projects.
• Ability to analyze technical problems, document your work, communicate clearly, and collaborate effectively.
• Curiosity, sound engineering judgment, and a willingness to learn in a fast‑moving, multidisciplinary environment.

Responsibilities

• 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.
• Collaborate with many different teams across both hardware and software development and testing.

Skills

Software development

Hardware architecture

Performance implications

Problem solving

Collaboration

Education

Electrical/Computer Engineering degree

Tools

PCI Express (PCIe)

DDR memory

Ethernet

Job description

Graphcore invites graduates to join our AI engineering campus in Austin as a Graduate Performance Engineer, contributing to design, integration, bring-up and validation of complex server- and rack-level performance in large-scale systems.

You will work with hardware and software teams to identify bottlenecks, model and evaluate the full stack, and develop practical optimization strategies while growing your practical technical skills.