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Graphcore

Delivers IPU-powered AI cloud services

Senior Power and Performance Validation Engineer

Hardware Validation & TestingConfirmed live in the last 24 hours
Full-timeBengaluru, Karnataka, IndiaNo salary listedIn-person

About the Job

Requirements

  • Strong experience in power and performance validation, silicon characterization or system performance engineering
  • Deep understanding of modern SoC architecture, including CPU, memory, interconnect and high-speed I/O technologies
  • Strong Linux systems knowledge and low-level performance analysis experience
  • Strong Python programming skills for automation, orchestration and data analysis
  • Experience with benchmarking and profiling tools such as stress-ng, fio, perf, iperf or equivalent technologies
  • Experience debugging complex hardware and software interactions
  • Ability to define structured validation methodologies, workload models and test strategies
  • Strong analytical skills with the ability to interpret large datasets and identify system bottlenecks
  • Strong communication and cross-functional collaboration skills
  • Ability to work independently on complex technical tasks while collaborating effectively across teams

Responsibilities

  • Define and lead validation strategies for power, thermal and performance characterization of AI compute silicon and platforms
  • Contribute to planning and execution of validation activities across multiple projects and milestones
  • Develop comprehensive validation plans covering functional, stress, workload and corner-case scenarios
  • Lead post-silicon bring-up and characterization activities for power and performance validation
  • Drive validation of CPU, memory, interconnect and high-speed I/O subsystems under complex workload conditions
  • Develop scalable automation frameworks, regression infrastructure and reporting tools using Python
  • Design and execute benchmark workloads, parameter sweeps and performance experiments to identify optimization opportunities
  • Collaborate with architecture, RTL, firmware, software and systems teams to debug and resolve complex technical issues
  • Define validation metrics, pass/fail criteria and reporting methodologies to ensure repeatable and high-quality analysis
  • Guide development of custom workload generators and micro-benchmarks where required
  • Analyse power, thermal and performance data to identify bottlenecks and recommend improvements
  • Contribute to continuous improvement of validation processes, tooling and engineering practices
  • Communicate technical findings, project status, risks and recommendations clearly to stakeholders and engineering leadership
  • Support knowledge sharing and contribute to continuous improvement across the validation organisation

Desired Qualifications

  • Experience with AI accelerator, GPU or high-performance compute architectures
  • Experience with pre-silicon modelling or simulation environments
  • Knowledge of power management technologies and silicon characterization methodologies
  • Programming experience in C/C++ for low-level system or benchmark development
  • Familiarity with hardware instrumentation and telemetry systems
  • Experience working with high core-count or large-scale compute systems
  • Experience contributing to shared validation infrastructure and engineering best practices

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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