At a Glance
- Tasks: Drive AI research, design experiments, and collaborate on next-gen AI hardware.
- Company: Join Graphcore, a leader in AI compute backed by SoftBank.
- Benefits: Flexible working, generous leave, private medical insurance, and a barista bar!
- Other info: Inclusive culture with opportunities for growth and collaboration across locations.
- Why this job: Make a real impact in the exciting field of AI and machine learning.
- Qualifications: Master’s or PhD in a technical field with strong Python and ML experience.
The predicted salary is between 60000 - 80000 £ per year.
At Graphcore, we’re building the future of AI compute. We’re a team of semiconductor, software and AI experts, with deep experience in creating the complete AI compute stack - from silicon and software to infrastructure at datacentre scale. 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.
Job Summary
As a research engineer at Graphcore, you will contribute to the advancement of AI research, investigating new ideas that push the limits on important AI/ML problems. Specialised hardware has been the key driver of the progress of AI over the last decade, and we believe that hardware‑aware AI algorithms and AI‑aware hardware developments will continue to be critical to advancing this exciting field. We are therefore looking for individuals who combine strong machine learning experience with practical engineering skills to deliver impactful AI research. We are seeking AI researchers with strong software engineering experience, particularly in lower‑level programming and performance optimisation for hardware efficiency. Our research spans a broad range of topics, including efficient training and inference, world models, life sciences, reinforcement learning, and beyond. You will work closely with researchers to generate ideas and translate them into scalable implementations, contributing to publications and projects that help to steer the future of AI hardware.
The Team
Graphcore Research participates in both fundamental and applied research, to characterise the computational requirements of machine intelligence and to demonstrate how hardware can drive the next generation of innovative AI models. We publish at leading AI/ML conferences (NeurIPS, ICML, ICLR) as well as specialist workshops, and collaborate with other research teams and organisations across the world. We pride ourselves on being a supportive and collaborative team, where we organise around our individual research interests to solve problems together in domains such as efficient compute, model scaling and distributed training and inference of AI models for multiple modalities and applications, including for sequence‑ and graph‑based data. We’re based across London, Cambridge and Bristol, with projects and discussions that involve all our locations.
Responsibilities and Duties
- Generate AI/ML ideas, design experiments, implement them & evaluate results.
- Prepare, submit & present your work to AI conferences and workshops.
- Provide technical insight to internal teams by designing experiments and delivering clear, actionable reports.
- Collaborate with researchers, silicon and software engineers at Graphcore to help define, build and test Graphcore’s next generation of AI hardware.
About you
- Master’s, PhD or equivalent experience in a technical discipline (e.g., Maths, Statistics, Computer Science, Physics, Chemistry).
- Python programming in a modern deep learning framework, e.g. PyTorch or JAX.
- Familiar with deep learning fundamentals: models, optimisation, evaluation and scaling.
- Capable of designing, executing and reporting from ML experiments.
- Lower‑level programming for hardware efficiency, e.g. C++/CUDA/Triton.
- Practical familiarity with hardware capabilities for deep learning – threads, caches, vector & matrix engines, data dependencies, bus widths and throttling.
- Practical familiarity with software stacks for deep learning – compilation, kernel fusion, XLA/ATen ops, streams, and asynchronous execution.
- Mathematics skills to support the above: calculus, probability theory and linear algebra.
- Experience submitting papers to international scientific conferences or workshops.
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. Applicants for this position must hold the right to work in the UK. Unfortunately at this time, we are unable to provide visa sponsorship or support for visa applications.
AI Research Engineer in Cambridge employer: graphcore
Contact Detail:
graphcore Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI Research Engineer in Cambridge
✨Tip Number 1
Network like a pro! Reach out to folks in the AI and tech community, especially those at Graphcore. Attend meetups, webinars, or conferences where you can connect with potential colleagues and learn more about their work.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your AI projects, experiments, and any papers you've published. This is your chance to demonstrate your expertise and passion for AI research.
✨Tip Number 3
Prepare for technical interviews by brushing up on your coding skills, especially in Python and lower-level programming. Practice solving problems related to AI/ML and be ready to discuss your thought process during interviews.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining the Graphcore team.
We think you need these skills to ace AI Research Engineer in Cambridge
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that align with the AI Research Engineer role. Highlight your machine learning experience, programming skills, and any relevant projects or publications to catch our eye!
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're passionate about AI research and how your background makes you a great fit for Graphcore. Share specific examples of your work and how it relates to the responsibilities outlined in the job description.
Showcase Your Projects: If you've worked on any interesting AI/ML projects, make sure to mention them! Whether it's a personal project or something from your studies, we love seeing practical applications of your skills and creativity.
Apply Through Our Website: We encourage you to apply directly through our website for a smoother application process. It helps us keep track of your application and ensures you’re considered for the role without any hiccups!
How to prepare for a job interview at graphcore
✨Know Your AI Fundamentals
Make sure you brush up on your deep learning fundamentals, especially around models, optimisation, and evaluation. Graphcore is looking for someone who can design and execute ML experiments, so be ready to discuss your past experiences and how they relate to the role.
✨Showcase Your Programming Skills
Since lower-level programming is key for this position, be prepared to talk about your experience with languages like C++ or CUDA. Bring examples of how you've optimised performance for hardware efficiency in your previous projects.
✨Prepare for Technical Discussions
Expect to dive deep into technical discussions during your interview. Familiarise yourself with hardware capabilities for deep learning and be ready to explain concepts like threads, caches, and data dependencies. This will show that you understand the intersection of hardware and AI.
✨Highlight Your Research Contributions
If you've submitted papers to conferences, make sure to mention them! Discussing your research and its impact will demonstrate your ability to contribute to Graphcore's mission. Be ready to share insights from your work and how they could apply to their projects.