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- Tasks: Join a team developing high-performance ML kernels for cutting-edge AI hardware.
- Company: Graphcore, a leader in AI innovation and part of the SoftBank Group.
- Benefits: Flexible working, generous leave, private medical insurance, and a vibrant office culture.
- Why this job: Make a real impact in AI while collaborating with experts in a dynamic environment.
- Qualifications: Degree in Computer Science or related field; experience in C/C++ and problem-solving skills.
- Other info: Inclusive workplace committed to diversity and continuous learning.
The predicted salary is between 28800 - 48000 ÂŁ per year.
Bristol, UK
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 Graduate Software Engineer 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 analytical reasoning to navigate unfamiliar domains.
Qualifications
- Bachelor or Master’s Degree in Computer Science, Maths, Machine Learning, Data Science, or related field
- Experience 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.
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. We take pride in our commitment to creating an inclusive and diverse workplace.
2026 Graduate Software Engineer - ML Kernels & Runtime Team in Bristol employer: graphcore
Contact Detail:
graphcore Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land 2026 Graduate Software Engineer - ML Kernels & Runtime Team in Bristol
✨Tip Number 1
Network like a pro! Reach out to current employees at Graphcore on LinkedIn or other platforms. Ask them about their experiences and any tips they might have for landing a role in the ML Kernels & Runtime Team.
✨Tip Number 2
Prepare for technical interviews by brushing up on your C++ skills and understanding linear algebra concepts. Practice coding challenges that focus on performance optimisation and memory-efficient designs to impress the interviewers.
✨Tip Number 3
Show your passion for AI and machine learning! During interviews, share your personal projects or coursework related to ML frameworks and parallel programming. This will demonstrate your commitment and enthusiasm for the field.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, you can keep an eye on any updates or new opportunities that pop up at Graphcore.
We think you need these skills to ace 2026 Graduate Software Engineer - ML Kernels & Runtime Team in Bristol
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the role. Highlight your experience with C/C++ and any relevant coursework in machine learning or numerical computing. We want to see how your skills align with what we're looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Share your passion for AI and performance optimisation, and explain why you’re excited about joining our team at Graphcore. Let us know what makes you tick!
Showcase Your Projects: If you've worked on any projects related to ML frameworks or code optimisation, make sure to mention them. We love seeing practical examples of your skills in action, so don’t hold back!
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of applications and ensures you get all the updates directly from us. Plus, it’s super easy!
How to prepare for a job interview at graphcore
✨Know Your Stuff
Make sure you brush up on your C/C++ skills, especially if you've worked with C++11. Familiarise yourself with linear algebra and numerical methods, as these are crucial for the role. Being able to discuss specific algorithms or optimisations you've implemented will show your technical prowess.
✨Show Your Problem-Solving Skills
Prepare to discuss past projects where you tackled complex problems. Think about how you approached debugging or performance optimisation. Graphcore values analytical reasoning, so be ready to explain your thought process and the trade-offs you considered.
✨Get Comfortable with Collaboration
Since the team thrives on collaboration, be prepared to talk about your experiences working in teams. Highlight instances where you received feedback and iterated on solutions. This shows you're open-minded and can work well in a fast-paced environment.
✨Ask Insightful Questions
Prepare some thoughtful questions about the team’s current projects or the technologies they use. This not only demonstrates your interest in the role but also gives you a chance to assess if the company culture aligns with your values, especially regarding innovation and continuous learning.
