At a Glance
- Tasks: Drive AI research, design experiments, and collaborate on next-gen AI hardware.
- Company: Join Graphcore, a leader in AI innovation and part of the SoftBank Group.
- Benefits: Enjoy flexible working, competitive salary, generous leave, and health benefits.
- Other info: Inclusive culture with opportunities for continuous learning and career growth.
- Why this job: Be at the forefront of AI breakthroughs and make a real impact.
- Qualifications: Master's or PhD in a technical field and experience in embodied AI or robotics.
The predicted salary is between 60000 - 80000 £ per year.
About Graphcore
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
As a researcher at Graphcore, you will contribute to the advancement of AI research, investigating new ideas that push the limits on important AI/ML problems. Specialized 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. As such, we're looking for candidates who are keen scientists and engineers, with the theoretical and practical skills needed for impactful AI research.
We are looking for researchers with experience of AI in low‑power, edge and embodied scenarios such as robotics, autonomous driving and augmented/virtual reality. We are interested in the training and deployment of multimodal AI models in these contexts, covering areas such as world models, real‑time computer vision, generating and reasoning over audio/video streams.
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.
Perhaps the best way to get an idea of what we're all about is to read one of our papers or an article on our blog. If you're excited to work at the cutting edge of AI supported by new hardware and want to develop your skills in this area, we'd love to hear from you!
Responsibilities and Duties
- Generate AI/ML ideas, design experiments, implement them & evaluate results.
- Prepare, submit & present your work to AI conferences and workshops.
- Collaborate with researchers, silicon and software engineers at Graphcore to help define, build and test Graphcore's next generation of AI hardware.
About you
Essential
- Master's, PhD or equivalent experience in a technical discipline (e.g., Maths, Statistics, Computer Science, Physics, Chemistry, Biomedical Engineering).
- Experience in embodied AI, world models or robotics.
- 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.
- Mathematics skills to support the above: calculus, probability theory and linear algebra.
- Experience submitting papers to international scientific conferences or workshops.
Desirable
- 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.
- Conference or workshop submissions in the fields of embodied AI, world models, or robotics.
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.
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.
Research Scientist (Visual Generative AI & World Models) in Cambridge employer: Job Search Place Limited
Graphcore is an exceptional employer, offering a dynamic and inclusive work culture that fosters continuous learning and innovation in the field of Artificial Intelligence. With a strong commitment to employee growth, we provide opportunities for impactful research, collaboration with diverse teams, and access to cutting-edge technology, all while enjoying benefits like flexible working, generous leave policies, and health support. Located in vibrant Bristol, our office features a barista bar and healthy snacks, making it a great place to thrive both personally and professionally.
StudySmarter Expert Advice🤫
We think this is how you could land Research Scientist (Visual Generative AI & World Models) in Cambridge
✨Tip Number 1
Network like a pro! Reach out to current or former employees at Graphcore on LinkedIn. A friendly chat can give you insider info and maybe even a referral, which can really boost your chances.
✨Tip Number 2
Show off your skills! Prepare a portfolio or a GitHub repository showcasing your projects related to AI, robotics, or any relevant research. This is your chance to demonstrate your hands-on experience and creativity.
✨Tip Number 3
Get ready for the interview! Brush up on your deep learning fundamentals and be prepared to discuss your past projects in detail. Practice explaining complex concepts in simple terms – it shows you really understand your stuff.
✨Tip Number 4
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 Research Scientist (Visual Generative AI & World Models) in Cambridge
Some tips for your application 🫡
Show Your Passion for AI:When writing your application, let your enthusiasm for AI and its potential shine through. We want to see that you're not just qualified, but genuinely excited about pushing the boundaries of what's possible in this field.
Tailor Your Experience:Make sure to highlight your relevant experience in embodied AI, world models, or robotics. We love seeing how your background aligns with our needs, so don’t hold back on showcasing your skills and projects that relate directly to the role.
Be Clear and Concise:Keep your application clear and to the point. We appreciate well-structured writing that gets straight to the heart of your qualifications and ideas. Avoid jargon unless it’s necessary, and make sure your passion comes across without fluff.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it gives you a chance to explore more about what we do at Graphcore!
How to prepare for a job interview at Job Search Place Limited
✨Know Your Stuff
Make sure you brush up on your knowledge of AI/ML concepts, especially in embodied AI and world models. Familiarise yourself with the latest research papers from Graphcore and other leading conferences like NeurIPS and ICML. This will not only help you answer technical questions but also show your genuine interest in the field.
✨Showcase Your Projects
Prepare to discuss your previous projects in detail, especially those involving Python programming and deep learning frameworks like PyTorch or JAX. Be ready to explain your thought process, the challenges you faced, and how you overcame them. This will demonstrate your practical skills and problem-solving abilities.
✨Collaborative Spirit
Graphcore values collaboration, so be prepared to talk about your experience working in teams. Share examples of how you've collaborated with others, whether in research or engineering contexts. Highlight your ability to communicate complex ideas clearly and work towards common goals.
✨Ask Insightful Questions
At the end of the interview, don’t forget to ask questions! Inquire about ongoing projects at Graphcore, the team dynamics, or future directions in AI research. This shows that you're not just interested in the job, but also in contributing to the company's vision and culture.