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Senior Power and Performance Validation Engineer

G
Graphcore

Graphcore is a Bristol-based AI chipmaker (IPU accelerators), a SoftBank subsidiary and a Molten Ventures portfolio company.

0 current maintainers0 active leads1 lead step-down1 early lead departureTeam intelligence

Maintainer signals as of 8/20/2026

About Graphcore

Graphcore (graphcore.ai) is a British semiconductor company building Intelligence Processing Units (IPUs) for AI workloads. Founded in Bristol in 2016, it was acquired by SoftBank in 2024. It is a portfolio company of Molten Ventures.

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Skills

Candidate Availability

Required and preferred rules are kept separate and reflect the wording in the original posting.

About the Role

You will define and lead power, thermal, and performance validation for AI compute silicon and platforms across pre-silicon and post-silicon environments. You will create validation plans, lead bring-up and characterization, develop Python automation and regression infrastructure, design benchmarks and workloads, analyze performance data, debug hardware and software interactions, and communicate findings and recommendations.

Requirements

  • Experience in power and performance validation, silicon characterization, or system performance engineering
  • Understanding of modern SoC architecture
  • Linux systems knowledge
  • Low-level performance analysis experience
  • Strong Python programming skills
  • Experience with benchmarking and profiling tools such as stress-ng, fio, perf, and iperf
  • Experience debugging hardware and software interactions
  • Ability to define validation methodologies, workload models, and test strategies
  • Analytical skills for interpreting large datasets and identifying bottlenecks

Responsibilities

  • Define and lead validation strategies for power, thermal, and performance characterization
  • Plan and execute validation activities across projects and milestones
  • Develop validation plans for functional, stress, workload, and corner-case scenarios
  • Lead post-silicon bring-up and characterization
  • Validate CPU, memory, interconnect, and high-speed I/O subsystems
  • Develop Python automation frameworks and regression infrastructure
  • Design benchmark workloads and performance experiments
  • Debug and resolve complex technical issues
  • Analyze power, thermal, and performance data
  • Communicate technical findings, risks, and recommendations