Senior Power and Performance Validation Engineer
Graphcore is a SoftBank-owned AI-compute company developing AI processors, systems, and software for machine-learning workloads.
Funding history
About Graphcore
Graphcore develops Intelligence Processing Units (IPUs) and the Poplar SDK for building and running machine-learning applications. It continues operating under the Graphcore name as a wholly owned SoftBank Group subsidiary.
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 validation strategies for power, thermal, and performance characterization across pre-silicon and post-silicon environments. You will develop validation plans and automation, run benchmarks and experiments, analyze system data, debug technical issues with cross-functional partners, and communicate findings and recommendations.
Requirements
- Experience in power and performance validation, silicon characterization, or system performance engineering
- Understanding of SoC architecture including CPU, memory, interconnect, and high-speed I/O
- Linux systems knowledge and low-level performance analysis experience
- Python programming for automation, orchestration, and data analysis
- Experience with benchmarking and profiling tools such as stress-ng, fio, perf, or iperf
- Experience debugging hardware and software interactions
- Ability to define validation methodologies, workload models, and test strategies
- Ability to interpret large datasets and identify system bottlenecks
Responsibilities
- Define and lead power, thermal, and performance validation strategies
- 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
- Develop Python automation, regression infrastructure, and reporting tools
- Design benchmark workloads and performance experiments
- Analyze power, thermal, and performance data to identify bottlenecks
- Collaborate to debug and resolve hardware and software issues
- Define validation metrics, pass-fail criteria, and reporting methodologies
- Communicate findings, risks, and recommendations to stakeholders