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

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

Cambridge Full-Time 60000 - 80000 £ / year (est.) Home office (partial)
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At a Glance

  • Tasks: Drive AI research, design experiments, and collaborate on next-gen AI hardware.
  • Company: Join Graphcore, a leader in AI innovation backed by SoftBank.
  • Benefits: Enjoy flexible working, generous leave, health plans, and a vibrant office culture.
  • Other info: Inclusive environment with excellent career growth and learning opportunities.
  • 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. 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. 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: Cerebras

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 leading experts, and access to cutting-edge technology in our vibrant Bristol office. Our comprehensive benefits package, including flexible working arrangements and generous leave policies, ensures that our team members thrive both personally and professionally.

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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 Cambridge

Tip Number 1

Get to know Graphcore! Dive into their research papers and blog posts to understand their work better. This will not only help you in interviews but also show your genuine interest in the company.

Tip Number 2

Network like a pro! Connect with current employees on LinkedIn or attend AI conferences where Graphcore is present. Building relationships can give you insider info and might even lead to a referral!

Tip Number 3

Prepare for technical interviews by brushing up on your Python skills and deep learning fundamentals. Practice coding challenges and be ready to discuss your past projects and how they relate to embodied AI and world models.

Tip Number 4

Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re serious about joining the team at Graphcore.

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

AI/ML Research
Python Programming
Deep Learning Frameworks (e.g., PyTorch, JAX)
Mathematics (Calculus, Probability Theory, Linear Algebra)
Experiment Design and Execution
Robotics
World Models

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 contributing to the field and pushing boundaries.

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!

Be Clear and Concise:Keep your application straightforward and to the point. We appreciate clarity, so avoid jargon where possible and make it easy for us to understand your qualifications and ideas.

Apply Through Our Website:We encourage you to submit your application directly through our website. It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it’s super easy!

How to prepare for a job interview at Cerebras

Know Your AI Fundamentals

Brush up on your deep learning fundamentals, especially around models, optimisation, and evaluation. Be ready to discuss how these concepts apply to embodied AI and world models, as this will show your understanding of the field.

Showcase Your Research Experience

Prepare to talk about your previous research projects, especially those involving AI in low-power or edge scenarios. Highlight any papers you've submitted to conferences, as this demonstrates your commitment to advancing the field and your ability to communicate complex ideas.

Familiarise with Graphcore's Work

Take some time to read Graphcore's papers or blog articles. Understanding their current projects and research focus will help you align your answers with their goals and show that you're genuinely interested in contributing to their mission.

Collaborative Mindset

Emphasise your ability to work collaboratively with diverse teams. Share examples of how you've successfully collaborated with engineers or researchers in the past, as this aligns with Graphcore's culture of teamwork and innovation.