Research Scientist (Visual Generative AI & World Models) New Cambridge, UK

Research Scientist (Visual Generative AI & World Models) New Cambridge, UK

Full-Time 60000 - 80000 £ / year (est.) No working from home possible
graphcore

At a Glance

  • Tasks: Drive AI research in visual generative modelling and world models with innovative experiments.
  • Company: Join Graphcore, a leader in AI compute backed by SoftBank.
  • Benefits: Enjoy flexible working, generous leave, health plans, and a vibrant office culture.
  • Other info: Collaborative team environment with opportunities for impactful publications and career growth.
  • Why this job: Be at the forefront of AI technology and shape the future of machine learning.
  • Qualifications: Master’s or PhD in a technical field with strong Python skills and research experience.

The predicted salary is between 60000 - 80000 £ per year.

About Graphcore

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 Scientist at Graphcore, you will advance AI research at the intersection of visual generative modelling, multimodal learning, world models and hardware‑aware machine learning. You will explore new model architectures, training methods and deployment strategies with applications in embodied AI, robotics and autonomous systems. Example research directions could include efficient video generation, diffusion and flow‑based models, multimodal representation learning, world models for agents, or analysis of how emerging generative AI workloads influence future AI accelerators. This role sits at the interface between frontier model research and AI hardware. Specialised hardware has been a key driver of AI progress 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 field. We are looking for researchers and engineers with the theoretical depth, practical judgement and implementation skills to turn ambitious ideas into rigorous experiments, publications and technical insights that influence the future of AI compute.

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, including NeurIPS, ICML and 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 individual research interests and solve problems together. Our work spans efficient compute, model scaling, distributed training and inference, and AI models for multiple modalities and applications, including 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

  • Develop and evaluate new ideas in visual generative AI, multimodal modelling and world models, from initial hypothesis through experiment design, implementation, analysis and publication.
  • Prepare, submit and present your work to AI conferences and workshops.
  • Work with researchers, software engineers and silicon teams to understand how emerging AI workloads can shape, and be shaped by, future Graphcore hardware and software systems.

About you

  • Master’s, PhD or equivalent experience in a technical discipline (e.g., Mathematics, Statistics, Computer Science, Physics, Chemistry, Biomedical Engineering).
  • Experience in visual generative AI, visual understanding or world models.
  • Strong Python programming skills using a modern deep learning framework, e.g. PyTorch or JAX.
  • Familiarity with deep learning fundamentals, including model architectures, optimisation, evaluation and scaling.
  • Ability to design, execute, analyse and clearly communicate ML experiments.
  • Mathematical foundations to support the above, including calculus, probability theory and linear algebra.
  • Evidence of research ability, such as conference or workshop submissions, publications, technical reports, open‑source projects or impactful industrial research.
  • Experience with multimodal reasoning or generation, action‑conditioned models, embodied AI, robotics or autonomous systems.
  • Lower‑level programming for hardware efficiency, e.g. C++/CUDA/Triton.
  • Practical familiarity with hardware considerations for deep learning, such as parallelism, memory hierarchy, vector and matrix engines, data movement, bandwidth limits and performance bottlenecks.
  • Practical familiarity with deep learning software stacks, such as graph compilation, kernel fusion, XLA/ATen operations, streams and asynchronous execution.

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. We take pride in our commitment to creating an inclusive and diverse workplace.

Research Scientist (Visual Generative AI & World Models) New Cambridge, UK employer: graphcore

Graphcore is an exceptional employer, offering a dynamic work culture that fosters collaboration and innovation at the forefront of AI research. With a commitment to employee growth, we provide opportunities for impactful contributions in a supportive environment, alongside competitive benefits such as flexible working, generous leave policies, and comprehensive health plans. Located in Cambridge, our team thrives on the synergy between cutting-edge research and advanced hardware development, making it an ideal place for those passionate about shaping the future of AI.

graphcore

Contact Details:

graphcore Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Research Scientist (Visual Generative AI & World Models) New Cambridge, UK

Tip Number 1

Network like a pro! Reach out to people in the AI field, especially those at Graphcore. Attend meetups, webinars, or conferences where you can connect with potential colleagues and learn more about the company culture.

Tip Number 2

Show off your skills! Prepare a portfolio of your projects related to visual generative AI and world models. Make sure to highlight any publications or impactful research you've done – this will make you stand out during interviews.

Tip Number 3

Practice makes perfect! Get ready for technical interviews by brushing up on your Python skills and deep learning frameworks like PyTorch or JAX. Consider mock interviews with friends or use online platforms to simulate the experience.

Tip Number 4

Apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you're genuinely interested in joining the Graphcore team. Don’t forget to tailor your application to reflect your passion for AI and hardware-aware algorithms!

We think you need these skills to ace Research Scientist (Visual Generative AI & World Models) New Cambridge, UK

Visual Generative AI
Multimodal Modelling
World Models
Python Programming
Deep Learning Frameworks (e.g., PyTorch, JAX)
Machine Learning Experiment Design
Mathematical Foundations (Calculus, Probability Theory, Linear Algebra)

Some tips for your application 🫡

Tailor Your Application:Make sure to customise your CV and cover letter for the Research Scientist role. Highlight your experience in visual generative AI and world models, and show us how your skills align with what we're looking for at Graphcore.

Show Off Your Research:We love seeing evidence of your research ability! Include any publications, conference submissions, or open-source projects that showcase your expertise in AI. This is your chance to shine!

Be Clear and Concise:When writing your application, keep it clear and to the point. Use straightforward language to explain your experience and ideas. We appreciate a well-structured application that’s easy to read.

Apply Through Our Website:Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. We can’t wait to hear from you!

How to prepare for a job interview at graphcore

Know Your Stuff

Make sure you brush up on the latest trends in visual generative AI and world models. Familiarise yourself with recent papers, especially those published at NeurIPS or ICML, as this will show your genuine interest and understanding of the field.

Showcase Your Skills

Prepare to discuss your experience with Python and any deep learning frameworks like PyTorch or JAX. Be ready to share specific examples of projects you've worked on, particularly those involving multimodal learning or hardware-aware machine learning.

Ask Smart Questions

During the interview, don’t hesitate to ask insightful questions about Graphcore’s research directions or how they integrate hardware with AI models. This not only shows your enthusiasm but also your critical thinking skills.

Practice Clear Communication

Since you'll need to present your work at conferences, practice explaining complex concepts in a simple way. Being able to communicate your ideas clearly is just as important as having them, so consider doing mock interviews with friends or colleagues.