Power and Performance Validation Engineer

Graphcore•Austin, TX

20h

About The Position

Graphcore is one of the world’s leading innovators in Artificial Intelligence compute. It is developing hardware, software and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry. As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone. Graphcore’s teams are drawn from diverse backgrounds and bring a broad range of skills and perspectives. A melting pot of AI research specialists, silicon designers, software engineers and systems architects, Graphcore enjoys a culture of continuous learning and constant innovation. Reporting to senior leadership within Architecture and Validation, the Power and Performance Validation Lead will drive validation strategy and execution for advanced AI compute silicon and systems. The role is responsible for leading power, thermal and performance validation activities across pre-silicon and post-silicon environments to ensure products meet efficiency, reliability and scalability expectations. This role requires strong technical expertise and collaboration across multiple engineering disciplines to deliver robust validation methodologies, scalable automation frameworks and actionable performance insights. The Power and Performance Validation team sits within the Architecture and Validation organisation and is responsible for validating the performance, efficiency and thermal behaviour of Graphcore silicon and systems. The team supports the full product lifecycle, from early architectural modelling through to first silicon bring-up, characterization and production readiness. Engineers work closely with cross-functional teams globally to debug complex issues, optimize workloads and continuously improve validation infrastructure and methodologies.

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

Nice To Haves

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

Responsibilities

Define and contribute 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
Work autonomously on 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