- Страна
- Великобритания
Откликайтесь
на вакансии с ИИ

2026 Summer Intern - Software Engineering - ML Kernels & Runtime Team
Исключительная возможность для старта карьеры в сфере AI-железа под эгидой SoftBank. Отличный социальный пакет для стажера и работа над передовыми технологиями (LLM, ускорители).
Сложность вакансии
Для стажировки уровень сложности выше среднего из-за требований к низкоуровневому программированию (C++), знанию линейной алгебры и специфики работы с аппаратным обеспечением. Кандидату потребуется понимание архитектуры процессоров и методов оптимизации памяти.
Анализ зарплаты
Для позиции стажера в Бристоле предлагаемая компенсация (обычно в районе £30,000-£40,000 в годовом исчислении) соответствует или слегка превышает рыночные стандарты для топовых технологических компаний Великобритании. Бристоль является крупным хабом полупроводниковой индустрии, и Graphcore держит планку на уровне лидеров рынка.
Сопроводительное письмо
I am writing to express my strong interest in the Software Engineering Intern position within the ML Kernels & Runtime Team at Graphcore. As a student with a deep interest in high-performance computing and numerical methods, I have followed Graphcore's innovations in AI hardware with great admiration. My background in C++ development and solid understanding of linear algebra align perfectly with the team's mission to deliver optimized compute kernels for next-generation AI accelerators.
During my academic projects, I have focused on performance-critical applications and low-level optimization. I am particularly excited about the opportunity to work on GEMM and tensor operations that power modern LLMs and CNNs. I am eager to apply my analytical reasoning to solve complex technical trade-offs and contribute to the robustness of your compute libraries through rigorous profiling and testing.
I am a collaborative problem-solver who thrives in fast-paced environments. Joining Graphcore would allow me to learn from world-class experts while contributing to the development of transformative AI infrastructure. Thank you for considering my application; I look forward to the possibility of discussing how my skills can support your team's goals.
Составьте идеальное письмо к вакансии с ИИ-агентом

Откликнитесь в graphcore уже сейчас
Присоединяйтесь к команде Graphcore и создавайте будущее ИИ-вычислений на острие технологий!
Описание вакансии
About Us
Graphcore is one of the world’s leading innovators in Artificial Intelligence compute.
It is developing hardware, software and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry.
As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone.
Graphcore’s teams are drawn from diverse backgrounds and bring a broad range of skills and perspectives. A melting pot of AI research specialists, silicon designers, software engineers and systems architects, Graphcore enjoys a culture of continuous learning and constant innovation.
Job Summary
We are looking for a Software Engineering Intern to join a team pioneering the development of high-performance machine learning (ML) kernels for a new generation of AI hardware.
In this role, you will contribute to building optimised compute kernels that support a wide range of ML operators—powering applications from convolutional neural networks (CNNs) to large language models (LLMs).
You'll leverage low-level programming and hardware-aware optimisation techniques to extract maximum performance and efficiency from modern accelerators. This is a unique opportunity to work at the intersection of ML, numerical computing, and scalable systems.
The Team
This is an exciting opportunity to join an expanding team at Graphcore. The Kernel Engineering team is responsible for delivering high performance compute library to help customers gain the maximum performance from AI hardware.
Responsibilities and Duties
- Supporting the design and implementation of kernels for linear algebra and tensor ops (GEMM, batched GEMM, convolutions, reductions, elementwise and fused operations) in C++
- Profile and optimise for the next generation of AI hardware - threading, cache locality, memory layout, and kernel launch efficiency.
- Support performance and correctness - add microbenchmarks, regression tests, numerics validation
- Debug issues, resolve bugs and generally improve the quality and functionality of the product
About you
You are open-minded and collaborative with interests in performance optimisation and memory-efficient designs, and you are looking to join a team of experts.
You are comfortable to discuss technical tradeoffs, receive feedback and iterate on solutions and you are drawn to technically challenging problems and use analyticals reasoning to navigate unfamiliar domains.
Essential:
- Bachelor or Master's Degree in Computer Science, Maths, Machine Learning, Data Science, or related field
- Experirence in C/C++11.
- Familiarity with Python or scripting tools for automation and testing.
- Understanding of linear algebra, numerical methods, or scientific computing.
- Good problem-solving skills and ability to work collaboratively in a fast-paced environment.
Preferred Qualifications:
- Courseworks or past experience in using ML frameworks, parallel programming, or code optimisation.
- Exposure to math libraries such as MKL or OpenBLAS.
- Knowledge of performance analysis tools.
Benefits
In addition to a competitive salary, Graphcore offers flexible working, a generous annual leave policy, private medical insurance and health cash plan, a dental plan, pension (matched up to 5%), life assurance and income protection. We have a generous parental leave policy and an employee assistance programme (which includes health, mental wellbeing, and bereavement support). We offer a range of healthy food and snacks at our central Bristol office and have our own barista bar! We welcome people of different backgrounds and experiences; we’re committed to building an inclusive work environment that makes Graphcore a great home for everyone. We offer an equal opportunity process and understand that there are visible and invisible differences in all of us. We can provide a flexible approach to interview and encourage you to chat to us if you require any reasonable adjustments.
Создайте идеальное резюме с помощью ИИ-агента

Навыки
- C++
- Python
- Linear Algebra
- Numerical Methods
- Machine Learning
- Parallel Programming
- Performance Optimization
- Profiling
- Git
Возможные вопросы на собеседовании
Проверка базовых знаний C++, критически важных для разработки ядер (kernels).
Объясните разницу между выделением памяти в стеке и в куче, и как это влияет на производительность в контексте высокопроизводительных вычислений?
Работа с тензорами требует отличного знания математики.
Как бы вы реализовали эффективное перемножение матриц (GEMM) для специфического оборудования, учитывая иерархию кэша?
Важно понимать, как кандидат подходит к поиску узких мест.
Какие инструменты или методики вы бы использовали для профилирования C++ кода, чтобы найти причину низкой пропускной способности памяти?
Проверка понимания параллелизма.
В чем разница между параллелизмом данных (SIMD) и многопоточностью, и когда уместно использовать каждый из подходов?
Оценка способности работать в команде и воспринимать критику.
Расскажите о случае, когда вы получили критический отзыв на свой код. Как вы на него отреагировали и что изменили в своем подходе?
Похожие вакансии
Applied Research Intern (Summer 2026)
Intern: Software Engineering, Multi-View 3D Reconstruction
Intern: Software Engineer, AI-enabled Robotic and Dexterous Manipulation Research
Software Engineer Intern, AI-Powered Picture Quality Tools
AI Intern
Omniverse AI Engineering intern
1000+ офферов получено
Устали искать работу? Мы найдём её за вас
Quick Offer улучшит ваше резюме, подберёт лучшие вакансии и откликнется за вас. Результат — в 3 раза больше приглашений на собеседования и никакой рутины!
- Страна
- Великобритания