ApplyBlast uses AI to match you with the right jobs, tailor your resume and cover letter, and apply automatically so you can land your dream job faster.

Features

Auto Apply Resume Optimizer Cover Letter Optimizer Interview Prep

Company

Social Media

Need Help?

team@applyblast.com

Principal Debug Validation Engineer at Graphcore - ApplyBlast

Principal Debug Validation Engineer

Graphcore

4 months ago

4.7 on Glassdoor

Bengaluru, India

Onsite

Full Time

Senior

0 applicants

View Job Listing

Apply to 100+ jobs

About this role

The Debug Validation Lead drives post-silicon debug and validation activities for next-generation AI compute silicon and systems. This role involves leading teams to identify, reproduce, and resolve complex hardware, firmware, and system-level issues during product bring-up and characterization. The position requires deep technical expertise in debugging methodologies and strong cross-functional collaboration with architecture, RTL, and software teams.

Responsibilities

Lead post-silicon debug and validation activities for AI compute platforms
Investigate and resolve complex silicon firmware and system-level issues
Develop structured debug methodologies and failure analysis processes
Collaborate with architecture and engineering teams to identify root causes
Analyze logs and hardware data to isolate system failures

Skills

About Graphcore

graphcore.ai

Headquarters

Bristol, England, United Kingdom

Company Size

501-1000 employees

Founded

2016

View Profile

Graphcore is a semiconductor and systems company that designs the Intelligence Processing Unit (IPU), a processor architecture purpose-built for machine intelligence to accelerate machine learning and AI workloads. It offers IPU-based servers and cloud access together with the Poplar software stack, compilers and developer tools to run training and inference at scale and integrate with common ML frameworks. Graphcore’s platform targets researchers and enterprises that need higher performance, efficiency and scalability for large models and intelligent applications across cloud and on‑prem deployments.