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

Electronics Laboratory Lead at Graphcore - ApplyBlast

Electronics Laboratory Lead

Graphcore

3 months ago

4.7 on Glassdoor

Bristol, England, United Kingdom

Onsite

Full Time

Manager

0 applicants

View Job Listing

Apply to 100+ jobs

About this role

The Electronics Laboratory Lead will own the safe and reliable operation of Graphcore’s Bristol electronics laboratories, ensuring that facilities, equipment, and infrastructure support critical engineering and operations work. This hands‑on leadership role involves managing test equipment, lab infrastructure, ESD controls, maintenance planning, and guiding a team of technicians to create dependable lab environments that accelerate hardware bring‑up, validation, and product testing.

Responsibilities

Own safe and reliable operation of the Bristol electronics laboratories
Manage test equipment, lab infrastructure, and ESD controls
Build, lead and mentor a team of laboratory technicians
Coordinate maintenance, calibration, and upgrades with subcontractors
Ensure health and safety standards are met across all lab activities

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.