Research Scientist (Visual Generative AI & World Models) in London

Research Scientist (Visual Generative AI & World Models) in London

London Full-Time 60000 - 80000 £ / year (est.) No working from home possible
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At a Glance

  • Tasks: Advance AI research in visual generative modelling and multimodal learning.
  • Company: Join Graphcore, a leader in AI compute backed by SoftBank.
  • Benefits: Enjoy flexible working, generous leave, private medical insurance, and more.
  • Other info: Collaborative team environment with opportunities for growth and innovation.
  • Why this job: Make a real impact on the future of AI with cutting-edge technology.
  • Qualifications: Master’s or PhD in a technical field and strong Python skills required.

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

Essential:

  • 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.

Desirable:

  • 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.

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 London employer: Cerebras

Graphcore is an exceptional employer located in the vibrant city of Bristol, offering a dynamic work culture that fosters innovation and collaboration. Employees benefit from competitive salaries, flexible working arrangements, and generous leave policies, alongside opportunities for professional growth in cutting-edge AI technology. With a focus on employee well-being, including private medical insurance, Graphcore stands out as a rewarding place to build a meaningful career.

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Contact Details:

Cerebras Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Research Scientist (Visual Generative AI & World Models) in London

Tip Number 1

Network like a pro! Reach out to people in the AI and research community, especially those connected to Graphcore. Attend conferences, workshops, or local meetups to make connections that could lead to job opportunities.

Tip Number 2

Show off your skills! Create a portfolio showcasing your projects in visual generative AI and world models. This could be anything from GitHub repositories to blog posts explaining your research. It’s a great way to demonstrate your expertise.

Tip Number 3

Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Be ready to discuss your past research and how it relates to Graphcore's work. Practice common interview questions with friends or mentors.

Tip Number 4

Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, you can keep an eye on new openings and updates directly from us.

We think you need these skills to ace Research Scientist (Visual Generative AI & World Models) in London

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 want to understand your thought process without getting lost in jargon.

Apply Through Our Website:Don’t forget to apply through our website! It’s the best way to ensure your application gets into the right hands. Plus, it shows us you’re serious about joining the Graphcore team.

How to prepare for a job interview at Cerebras

Know Your Stuff

Make sure you brush up on your knowledge of visual generative AI and world models. Be ready to discuss your previous research, especially any publications or projects that relate to the role. This shows you're not just familiar with the theory but can also apply it practically.

Show Off Your Skills

Prepare to demonstrate your Python programming skills, particularly with frameworks like PyTorch or JAX. You might be asked to solve a coding problem or explain your approach to a specific ML experiment, so practice articulating your thought process clearly.

Understand the Hardware

Since this role sits at the intersection of AI research and hardware, make sure you have a solid grasp of how hardware influences AI models. Familiarise yourself with concepts like parallelism and memory hierarchy, as well as how they relate to your research.

Be Collaborative

Graphcore values teamwork, so be prepared to discuss how you've worked with others in past projects. Highlight your ability to communicate complex ideas clearly and how you’ve contributed to a collaborative research environment.