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Graphcore

Delivers IPU-powered AI cloud services

Graduate Machine Learning Engineer

Applied Machine LearningUpdated on Nov 10
Full-timeBristol, UK£45k /yrIn-person

About the Job

Requirements

  • A Bachelor's or Master's degree in Machine Learning, Computer Science, Mathematics, Data Science, or a related field.
  • Software development skills and proficiency with a deep learning framework such as PyTorch or JAX.
  • Understanding of deep learning architectures, optimisation, evaluation and scaling, and the ability to design, run and explain machine-learning experiments.
  • A collaborative approach and willingness to work through unfamiliar technical problems, ask questions and take responsibility.
  • Ability to demonstrate relevant skills through coursework, a dissertation, personal or team projects, research, or other relevant experience.

Responsibilities

  • Implement, train and optimise advanced models on next-generation hardware, connecting research ideas with systems running across thousands of accelerators.
  • Benchmark models, use profiling to find performance bottlenecks, design experiments and contribute fixes across models, software and accelerator systems.
  • Work with Research, Software and Product teams to test ideas that could inform future hardware.
  • Conduct experiments to understand what makes a model accurate, efficient and ready to scale.
  • Work across low-level kernel optimisation and implementation of research-level algorithms for new AI models.
  • Build technical range through hands-on work across AI models and accelerator systems during the two-year programme.
  • Identify opportunities to innovate and differentiate the company’s technology across accelerator hardware, its software stack and AI applications.

About the Company

Graphcore

Delivers IPU-powered AI cloud services

Graphcore.ai focuses on building and delivering Intelligence Processing Units (IPUs) and related AI services for enterprises. It provides IPU-powered cloud services, pre-trained AI models, optimized inference engines, and APIs on a subscription basis with on-demand pricing and free tiers through cloud partners. The IPUs accelerate AI workloads and enable scalable, cost-efficient AI deployment in enterprise applications. The company differentiates itself through specialized IPU hardware and optimized software stack, plus partnerships with cloud providers to reach customers, rather than relying on generic hardware. The goal is to help businesses scale AI-powered products and operations efficiently by offering flexible, scalable compute and ready-to-use AI components.

Company size
501-1,000
Company stage
Growth Equity (Non-Venture Capital)
Total funding
$1.1B
Headquarters
Bristol, United Kingdom
Founded
2016

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