---
title: 'Software Engineer Summer Intern, AI Compute Libraries & Performance 2027 at Graphcore'
canonical: 'https://feeny.ai/job/software-engineer-summer-intern-ai-compute-libraries-performance-2027-graphcore-58c3xgmqptpe'
type: 'job'
last_seen: '2026-10-20'
---

# Software Engineer Summer Intern, AI Compute Libraries & Performance 2027 at Graphcore

- **Company:** Graphcore
- **Location:** Bristol, United Kingdom
- **Posted:** 2026-10-20
- **Last confirmed live:** 2026-10-20
- **Apply:** https://job-boards.greenhouse.io/graphcore/jobs/8894868002

## Job description

Location: Bristol, UK Salary: £2500 per month Start date: June 2027 Application deadline: Midnight, 29th November 2026 We encourage you to apply early, as we may close applications before the advertised deadline.

The Internship Programme at Graphcore

Explore a career at Graphcore through a 12-week summer internship, gaining hands-on experience on real projects. You’ll bring fresh ideas, put your learning into practice and help shape what we’re creating. Along the way, you’ll tackle challenging problems with a team who welcome your questions and support you as you build your skills and confidence.

## What you’ll work on

Use your programming skills and curiosity to help AI models run efficiently on next-generation Graphcore hardware.

In AI Compute Libraries & Performance, you’ll contribute to C++ libraries and compute kernels for machine learning workloads. Your work will include:

- Developing compute kernels: Implement and improve operations such as matrix multiplication (GEMM), convolutions, reductions, elementwise operations and fused kernels that combine multiple operations.
- Understanding and improving performance: Use profiling and microbenchmarks to measure execution speed and investigate how threading, cache locality, memory layout and kernel launch efficiency affect performance.
- Checking correctness and reliability: Build regression tests and numerical checks, investigate issues and improve the quality of the libraries our customers use.

Through these projects, you’ll develop practical experience connecting numerical computing with how code runs on hardware, helping deliver software that is fast, accurate and reliable.

## Your team and support

You’ll join a team building high-performance compute libraries that help customers get more from Graphcore hardware. Our work brings together machine learning, numerical computing and accelerator performance, with colleagues sharing their expertise to solve engineering problems.

You’ll contribute to clearly scoped projects and build your skills with guidance from engineers working in performance and low-level software. Together, we use profiling, experiments and technical reviews to compare approaches, understand trade-offs and improve our solutions.

Your buddy will help you settle in, get familiar with our tools and ways of working, and find the right people to ask. Your manager will meet with you regularly to agree goals, offer feedback and discuss your development, including time for learning.

We welcome different perspectives and make space for everyone to contribute. Questions, alternative approaches and requests for help are part of how we work. As you take on more responsibility, your colleagues will help you work through challenges, and your ideas will be listened to and discussed respectfully.

## How you’ll learn and grow

Over the 12 weeks, you’ll build performance engineering skills through hands-on work on compute kernels, benchmarks and tests.

Profiling and experiments will help you understand where time is spent and how changes to code and data layout affect performance. Numerical validation and regression testing will show you how to check that an optimisation preserves correct results and continues to work as software changes.

Working with specialists and discussing technical trade-offs will help you develop your engineering judgement, explain your findings and connect mathematical operations to efficient implementations on hardware.

## What we're looking for

- Currently studying towards a bachelor’s or master’s degree in Computer Science, Maths, Machine Learning, Data Science or a related field
- Experience with C or C++11, plus familiarity with Python or scripting tools for automation and testing
- An understanding of linear algebra, numerical methods or scientific computing
- Problem-solving skills and collaborative approach to unfamiliar technical challenges

Previous industry experience is not required. Tell us what you built or investigated through coursework, personal or team projects or other relevant experience, how you approached it and what you learned.

Coursework or experience with machine learning frameworks, parallel programming, code optimisation, maths libraries or performance analysis would be useful. These are additional strengths, rather than essential requirements.

## Benefits

- Flexible working: Find a balance between your internship and life outside work
- 5 days of annual leave: Take time to rest and recharge during your 12-week internship
- Life in the office: Get to know your colleagues in spaces designed for collaboration, with free food, a great selection of ice cream and an on-site barista
- Learning and development: Build your skills and explore your interests with access to O’Reilly, our online learning platform

We welcome people from all backgrounds and experiences and are committed to building an inclusive environment where everyone can do their best work.

We’re an equal opportunity employer and recognise that everyone brings different strengths and perspectives. If you need any adjustments during the interview process, just let us know - we’re happy to support you.

Sponsorship

Applicants must already have the right to work in the UK for the full duration of the programme, without requiring visa sponsorship. We are unable to sponsor work visas for our Early Careers opportunities.

Introduction to Graphcore

At Graphcore, we’re building next generation AI compute: From semiconductors and software to systems at datacenter scale. We are proud to be owned by SoftBank Group and work with other companies in the SoftBank family to deliver AI compute to customers working at the AI frontier. Starting your career here means working alongside people with different backgrounds and expertise, from AI researchers to chip designers and software engineers. You’ll learn from each other, bring fresh ideas and help solve challenging problems together.

How to apply and what to expect

To apply, answer the application questions below and upload your CV and cover letter. We’ll let you know the outcome of your application by early December at the latest. If successful, you’ll be invited to complete a technical assessment. Candidates who reach the final stage will then be invited to attend in-person assessments in early spring.

Curious about where your skills could take you? Apply for a summer internship at Graphcore and help us build what comes next.

## About Graphcore

## Company Overview
- **One-liner**: Graphcore designs and builds the Intelligence Processing Unit (IPU), a processor purpose-built for machine intelligence, and provides a complete AI compute stack from silicon to software.
- **Entity Type**: Private (wholly owned subsidiary of SoftBank Group Corp as of 2025/2026)
- **Headquarters**: Bristol, England, UK
- **Founded**: 2016
- **Founders**: Nigel Toon and Simon Knowles

## Core Business
- **Primary industry**: AI hardware/accelerators, semiconductor design, AI software platform
- **Target customers**: Cloud providers (Microsoft Azure), enterprises, AI researchers, hyperscalers
- **Mission statement**: “Let innovators create the next breakthroughs in machine intelligence to enhance human potential”

## Products & Services
- **[IPU (Intelligence Processing Unit)](https://www.graphcore.ai/)**: A processor designed from the ground up for machine intelligence workloads; uses a massively parallel architecture (MIMD) with fine-grained compute and on-chip memory.
- **[IPU-Machine M2000](https://www.graphcore.ai/about)**: Second-generation IPU platform – a 1U server appliance housing 4 MK2 GC200 IPU processors, delivering an 8× performance uplift over the first generation.
- **[C2 IPU Accelerator PCIe Card](https://www.graphcore.ai/about)**: PCIe form factor accelerator for server integration, first demonstrated at ICML 2018.
- **[Poplar Software Stack](https://www.graphcore.ai/)**: Full SDK and framework integration (PyTorch, TensorFlow) that lets developers target the IPU directly.

## Market Standing
- **Valuation/Market Cap**: Acquired by SoftBank Group Corp (amount undisclosed); prior to acquisition valued at $2.77 B (Series E, lead by Ontario Teachers’ Pension Plan Board).
- **Key Metric**: Total funding raised prior to acquisition – over $680 M across Series A through E.
- **Notable Investors/Partners**: SoftBank (owner), Microsoft (customer and investor), BMW, Samsung, Dell Technologies, Bosch, Sequoia Capital, Atomico, Fidelity, Baillie Gifford, Ontario Teachers’.
- **Growth Signals**: Part of the fast-growing SoftBank AI ecosystem; expanding teams globally (Bristol, London, Cambridge, Gdańsk, Hsinchu, Bengaluru); first customer (Microsoft Azure) live since 2018.

## Competitive Advantages
- **First purpose-built AI processor**: The IPU architecture is fundamentally different from GPUs – designed specifically for the sparse, parallel nature of neural network computation.
- **Full stack ownership**: Graphcore controls silicon, system hardware, and software (Poplar), enabling tight optimisation across the entire compute chain.
- **Cloud + on‑prem availability**: IPUs are available in the cloud on Microsoft Azure and as hardware from Dell, giving customers flexible deployment options.
- **Strong IP and ecosystem**: 99+ engineering staff; deep expertise in semiconductor, systems, and AI software, backed by long-term SoftBank investment.

## Strategic Focus
- **Scale AI infrastructure**: Delivering key technology into SoftBank’s global AI ecosystem and expanding the IPU platform to meet growing demand for AI compute.
- **Expand into new regions**: Opening offices and hiring in India (Bengaluru) and across Europe (Gdańsk, London, Cambridge) to accelerate R&D and customer support.
- **Democratise AI**: Continuing to lower the barrier for machine intelligence by providing accessible, high-efficiency hardware and software for innovators worldwide.

## Why Work Here
- **Flexible hybrid work**: Employees are expected on-site three days a week, with trust and flexibility to balance work and life.
- **Comprehensive benefits**: Unlimited annual leave, private medical insurance (UK), dental & health cash plan, income protection, life assurance, pension matched up to 5%, generous parental leave, and a personal development plan.
- **Culture and growth**: ML reading groups, board game socials, book clubs, yoga, running, watersports, team events; strong DE+I initiatives; ambitious but supportive environment.
- **Perks**: Free barista‑made coffee, snacks, and wellbeing rooms; cycle‑to‑work scheme; gym membership discount; education/training allowances.
- **Purpose-driven work**: Opportunity to shape the future of AI compute and see your contributions used by global innovators.

## Sources
1. [graphcore.ai/about](https://www.graphcore.ai/about)
2. [graphcore.ai/](https://www.graphcore.ai/)
3. [graphcore.ai/careers](https://www.graphcore.ai/careers)
4. [graphcore.ai/jobs](https://www.graphcore.ai/jobs)
5. [builtin.com/company/graphcore](https://builtin.com/company/graphcore)

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