AI Research Engineer (Hardware-Aware Machine Learning) at Graphcore (London, Cambridge or Bristol, UK)

Job Description

Graphcore is hiring an AI research engineer for Graphcore Research, working on hardware-aware machine-learning algorithms and on how new AI hardware can enable the next generation of models. The same role is posted for London, Cambridge and Bristol.

At a glance

• Position: AI Research Engineer
• Where: London, Cambridge or Bristol, UK
• Pay: Competitive salary (no figure stated)
• Type: Full time
• Visa: UK right to work required; no visa sponsorship
• Apply: open until filled (re-checked 13 November 2026)

About the AI research engineer role at Graphcore

• Generate machine-learning research ideas, design and run experiments, and evaluate the results
• Write up, submit and present work at AI conferences and workshops
• Design experiments and write clear, actionable reports that give technical insight to internal teams
• Work with researchers and silicon and software engineers to define, build and test Graphcore’s next generation of AI hardware

According to the posting, Graphcore Research covers both fundamental and applied work: efficient training and inference, model scaling, distributed training, world models, reinforcement learning, life sciences, and models for sequence and graph data. The team publishes at NeurIPS, ICML and ICLR and works across its three UK sites.

Why this role matters

Most machine-learning research treats the hardware as fixed. At a chip company the arrow runs both ways: algorithm results can shape the next accelerator, and hardware features can make new algorithms practical. For an ML researcher who is comfortable with CUDA or Triton and wants to see their work influence silicon, this is one of the few places in Europe to do it.

What Graphcore is looking for

• A master’s, PhD or equivalent experience in a technical field such as mathematics, statistics, computer science, physics or chemistry
• Python in a modern deep-learning framework such as PyTorch or JAX, and a good grasp of deep-learning models, optimisation, evaluation and scaling
• The ability to design, run and report on machine-learning experiments
• Lower-level programming for hardware efficiency, such as C++, CUDA or Triton
• Practical familiarity with deep-learning hardware (threads, caches, vector and matrix engines, bus widths, throttling) and software stacks (compilation, kernel fusion, XLA/ATen ops, asynchronous execution)

Nice to have

• Mathematics supporting the above: calculus, probability and linear algebra
• Experience submitting papers to international conferences or workshops

Pay and location

Graphcore offers a competitive salary but does not state a figure. Benefits named in the posting include flexible working, private medical and dental cover, a pension matched up to 5%, and parental leave. Applicants must already have the right to work in the UK; Graphcore says it cannot currently sponsor visas.

How to apply

Apply through the official Graphcore job posting. Graphcore’s posting does not give a closing date, so the role is open until filled; ResearchJobs.in will re-check this listing on 13 November 2026. Check the posting for location and work-authorisation details before you apply.

See all our artificial intelligence jobs, or browse more research jobs on ResearchJobs.in.