2026 Platform QA Intern, Graphcore
2+ days a week in office
Advanced AI systems and services
Be an early applicant
Advanced AI systems and services
501-1000 employees
Be an early applicant
2+ days a week in office
501-1000 employees
Company mission
To make machine learning faster, easier and more intelligent.
Role
Who you are
- Currently studying towards and Undergraduate/ Master’s Degree in Computer Science, or similar degree
- Strong relevant programming experience Python/Go/C++/infrastructure-as-code scripting or related to the domain
- Experience working in Linux environments
- Automation of building/testing with continuous integration systems
- Strong impartial report writing optimised for the reader
- Aptitude for planning, constructing, and executing responsibilities & duties above
Desirable
- Domain experience of the products under test: Containerisation (e.g. Docker), Virtualisation and Provisioning, Workload and job scheduling (e.g. Kubernetes, Ray) on high core-count machines and rack-scale installations
- Experience in quality assurance/testing teams
- Experience with the Atlassian suite and CI/CD platforms such as Jenkins; GitHub or GitLab actions
What the job involves
- As part of the SoftBank Group, backed by significant long-term investment, we are delivering key technology into the fast-growing SoftBank AI ecosystem
- To meet the vast and exciting AI opportunity, Graphcore is expanding its teams around the world
- We are bringing together the brightest minds to solve the toughest problems, in a place where everyone has the opportunity to make an impact on the company, our products and the future of artificial intelligence
- We are looking for an intern to join our Platform Quality Assurance group
- You will learn how to creatively exercise our product and provide feedback to the engineering delivery and product management teams
- This helps them make decisions about engineering effort and the trajectory of the product
- Working in either the component Quality Assurance team you will develop a close working relationship with the relevant development teams; or working in the integration Quality Assurance exercising the aggregated and composed system at a much larger scale with a bias towards informing the product management team
- You will provide valuable observations and measurements of the product, looking beyond the natural focus of the delivery and product teams, painting a comprehensive behavioural picture of the product in typical and atypical scenarios
- Supporting the execution of tests and reports optimised for the different decision-making readers including delivery engineering and the product management teams
- Supporting the organisation of a repository of results & collaboration with the QA team
- Developing or refining your skills in the domain area of the product component or the system in aggregate and at scale
- Specific domains include Workload Management (Kubernetes, Ray, and so on); Cloud Development; Management & Observability
Our take
The hardware required to train AI models comes at a high cost, both financially and environmentally, producing millions of dollars in expenses and hundreds of tons of greenhouse gases. In response, Graphcore develops accelerator chips designed to expedite AI system training while significantly reducing power consumption.
AI accelerators like those crafted by Graphcore specialise in enhancing specific AI applications, such as artificial neural networks, deep learning, and machine learning. Utilising multicore designs and prioritising low-precision arithmetic or in-memory computing, these accelerators elevate the performance of large AI algorithms, achieving breakthrough results in natural language processing and computer vision.
Graphcore has ambitious plans to create an AI supercomputer, aiming to be one of the most powerful in its class. However, progress on this has extended beyond its planned 2024 debut, and the company was purchased by Softbank later that year. Though the acquisition by the Japanese multinational lowered Graphcore's valuation and highlighted structural problems in the local financing of UK tech pioneers, the buyout will undoubtedly aid the company in its ambitions to shape the future of AI computing.
Freddie
Company Specialist at Welcome to the Jungle
Insights
Company
Funding (last 2 of 6 rounds)
Dec 2020
$222m
SERIES E
Feb 2020
$150m
SERIES D
Total funding: $682m
Company benefits
- Work-Life Balance: We believe you should have a good work-life balance. Everyone's situation is different, so we offer flexible working arrangements and start and finish times, allowing you to choose when to work from home or come into the office
- Wellbeing: We want to ensure that our employees have the resources and support they need to prioritise their health and wellbeing
- Healthcare: We offer Private Medical Insurance (PMI) to our employees to help them take care of their health and that of their loved ones
- Progression: We prioritise learning and development as an integral part of our culture at Graphcore. Our Talent Development team is dedicated to equipping all our employees with the necessary tools, resources, and support to enhance their skills and reach their full potential in their careers
- Pension: We believe that our employees deserve the best when it comes to planning for their future
- Income Protection: Graphcore understands that unforeseen circumstances can happen, and we want to ensure our employees have the necessary financial security in place
Company HQ
Old City, Bristol, UK
Leadership
Nigel Toon
(Co-Founder & Exec Chair)Previously the President and CEO at picoChip Designs (processors for telecoms). As well as the VP and GM of Europe at Altera (semiconductors, merged with Intel).
Simon Knowles
(Co-Founder & CTO)Founded two successful semiconductor companies, Element14 and Icera, for a combined value of over $1 billion.
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