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Graphcore

Delivers IPU-powered AI cloud services

Director of Product Engineering

Engineering LeadershipConfirmed live in the last 24 hours
Full-timeIn-person

About the Job

Requirements

  • Extensive capability in semiconductor product engineering, test engineering, or manufacturing engineering.
  • Proven people leadership experience, including hiring and building teams across geographies.
  • Strong understanding of semiconductor, PCBA, and system-level manufacturing and testing.
  • Deep statistical analysis skills, including statistical process control, design of experiments, regression, hypothesis testing, and Six Sigma methods.
  • Ability to analyze large manufacturing datasets using Python, SQL, JMP, or similar tools.
  • Success driving yield, quality, and cost improvements in high-volume production.

Responsibilities

  • Lead how Graphcore products move through launch and high-volume production.
  • Recruit and develop a team focused on semiconductor and PCBA manufacturing performance.
  • Shape yield, quality, and cost across chip manufacturing, test, PCBA, and system-level production.
  • Provide teams with the data, standards, and direction needed to solve production problems.
  • Work with OSATs, test engineering, manufacturing, quality, data engineering, and analytics teams.
  • Define best practices for data collection, correlation, dashboards, and self-service manufacturing insight.
  • Set the standard for product engineering across Graphcore’s manufacturing lifecycle.
  • Set direction, remove ambiguity, and build capability across locations.

About the Company

Graphcore

Delivers IPU-powered AI cloud services

Graphcore.ai focuses on building and delivering Intelligence Processing Units (IPUs) and related AI services for enterprises. It provides IPU-powered cloud services, pre-trained AI models, optimized inference engines, and APIs on a subscription basis with on-demand pricing and free tiers through cloud partners. The IPUs accelerate AI workloads and enable scalable, cost-efficient AI deployment in enterprise applications. The company differentiates itself through specialized IPU hardware and optimized software stack, plus partnerships with cloud providers to reach customers, rather than relying on generic hardware. The goal is to help businesses scale AI-powered products and operations efficiently by offering flexible, scalable compute and ready-to-use AI components.

Company size
501-1,000
Company stage
Growth Equity (Non-Venture Capital)
Total funding
$1.1B
Headquarters
Bristol, United Kingdom
Founded
2016

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