Graduate ML Engineer: Build Scalable AI Systems

Graphcore Early Careers; West of England; Presencial; GBP 30 000 - 42 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Up to 5% matched pension

Phantom equity

Thoughtfully designed office spaces +

Free food and on-site barista

Income protection and life assurance

Electric Vehicle Scheme (salary sac)

Flexible benefits (private medical, +)

Dental cover

Health cash plan

Private medical insurance

Cycle to work scheme

Give as you earn

Resumo da oferta

Graphcore invites graduates to join the Applied AI track on a two-year programme in Bristol, UK. From day one, you’ll own initiatives, learn across AI models and accelerator systems, and work with cross-disciplinary teams to turn theory into scalable AI solutions.

You’ll contribute to benchmarking, profiling, and experimental design aimed at improving model accuracy, efficiency, and deployment readiness on Graphcore hardware.

Qualificações

• Bachelor/Master's degree in Machine Learning, Computer Science, Maths, Data Science, or 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 for ML experiments.

Responsabilidades

• Test ideas that could inform future hardware and contribute fixes across models, software and accelerator systems.
• Work with Research, Software and Product teams to run experiments that improve model accuracy and efficiency.
• Benchmark models, profile performance bottlenecks and design experiments across AI systems.

Conhecimentos

PyTorch

JAX

Deep learning concepts

Collaboration

Formação académica

Bachelor/Master's degree in Machine Learning, Computer Science, Maths, Data Science, or related field

Descrição da oferta de emprego

Graphcore invites graduates to join the Applied AI track on a two-year programme in Bristol, UK. From day one, you’ll own initiatives, learn across AI models and accelerator systems, and work with cross-disciplinary teams to turn theory into scalable AI solutions.

You’ll contribute to benchmarking, profiling, and experimental design aimed at improving model accuracy, efficiency, and deployment readiness on Graphcore hardware.