Hardware-Aware AI Research Engineer

EngineersOfAI; Greater London; On-site; GBP 65,000 - 90,000; Full time

Job summary

Graphcore, a leading AI compute company, invites researchers to advance AI hardware-aware ML. You will design experiments, implement scalable AI methods and contribute to publications, collaborating with researchers, silicon and software engineers.

We welcome candidates with a strong ML background, PhD or equivalent, experience in Python and lower-level programming for hardware efficiency, and a passion for pushing the boundaries of AI hardware and software tooling.

Qualifications

• Master’s, PhD or equivalent experience in a technical discipline (e.g., Maths, Statistics, Computer Science, Physics, Chemistry).
• 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.
• 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

Responsibilities

• Generate AI/ML ideas, design experiments, implement them and evaluate results.
• Prepare, submit and present your work to AI conferences and workshops.
• Provide technical insight to internal teams by designing experiments and delivering clear, actionable reports.
• Collaborate with researchers, silicon and software engineers at Graphcore to help define, build and test Graphcore’s next generation of AI hardware.

Skills

Python programming in DL framework (Py

Education

Master’s/PhD or equivalent

Tools

PyTorch

JAX

Job description

Graphcore, a leading AI compute company, invites researchers to advance AI hardware-aware ML. You will design experiments, implement scalable AI methods and contribute to publications, collaborating with researchers, silicon and software engineers.

We welcome candidates with a strong ML background, PhD or equivalent, experience in Python and lower-level programming for hardware efficiency, and a passion for pushing the boundaries of AI hardware and software tooling.