Research Scientist: Visual Generative AI & World Models

EngineersOfAI; Bristol; On-site; GBP 90,000 - 120,000; Full time

Job summary

Graphcore, based in Bristol with teams across the UK, is seeking a Research Scientist to advance AI research at the intersection of visual generative modelling, multimodal learning and hardware-aware ML. You will explore new architectures and training methods with applications in embodied AI, robotics, and autonomous systems.

This role sits at the frontier of model research and AI hardware, requiring depth in theory, practical judgment and implementation to drive experiments, publications and

Qualifications

• Master’s, PhD or equivalent experience in a technical discipline.
• 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 experiments.

Responsibilities

• 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.

Skills

Python programming

Deep learning fundamentals

Visual generative AI

World models

PyTorch

JAX

Education

Master’s or PhD in a technical discipline

Tools

PyTorch

JAX

Job description

Graphcore, based in Bristol with teams across the UK, is seeking a Research Scientist to advance AI research at the intersection of visual generative modelling, multimodal learning and hardware-aware ML. You will explore new architectures and training methods with applications in embodied AI, robotics, and autonomous systems.

This role sits at the frontier of model research and AI hardware, requiring depth in theory, practical judgment and implementation to drive experiments, publications and