Machine Learning Engineer (Large Systems)
Machine Learning Engineer (Large Systems)

Machine Learning Engineer (Large Systems)

London Full-Time 36000 - 60000 £ / year (est.) No home office possible
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At a Glance

  • Tasks: Develop and optimise AI models for cutting-edge hardware, collaborating with various teams.
  • Company: Join Graphcore, a leader in AI technology innovation and optimisation.
  • Benefits: Enjoy flexible working, generous leave, private medical insurance, and healthy snacks at the office.
  • Why this job: Make a tangible impact in AI while working in a dynamic, collaborative environment.
  • Qualifications: Bachelor’s or higher in relevant fields; strong skills in Python and deep learning frameworks required.
  • Other info: Diversity is valued; flexible interview arrangements available.

The predicted salary is between 36000 - 60000 £ per year.

As a Machine Learning Engineer in the Applied AI team at Graphcore, you will contribute to advancing AI technology by developing and optimising AI models tailored to our specialised hardware. Working closely with the Software development and Research teams, you will play a critical role in finding opportunities to innovate and differentiate Graphcore’s technology. We seek engineers with strong technical skills and an understanding of AI model implementation, eager to make a tangible impact in this rapidly evolving field.

The Team

The Applied AI team’s role is to be proxies for our customers; we need to understand the latest AI models, applications, and software to ensure that Graphcore’s technology works seamlessly with the AI ecosystem. We build reference applications, contribute to key software libraries (e.g., optimizing kernels for efficiency on our hardware), and collaborate with the Research team to develop and publish novel ideas in domains such as efficient compute, model scaling, and distributed training and inference of AI models for multiple modalities and applications.

If you\’re excited about advancing the next generation of AI models on cutting-edge hardware, we’d love to hear from you!

Responsibilities and Duties

  1. Implement the latest machine learning models and optimise them for performance and accuracy, scaling to thousands of accelerators.
  2. Test and evaluate new internal software releases, provide feedback to software engineering teams, make vital code fixes, and conduct code reviews.
  3. Benchmark models and key ML techniques to identify performance bottlenecks and improve model efficiency.
  4. Design and conduct experiments on novel AI methods, implement them, and evaluate results.
  5. Collaborate with Research, Software, and Product teams to define, build, and test Graphcore’s next generation of AI hardware.
  6. Engage with the AI community and stay updated with the latest developments in AI.

Candidate Profile

Essential skills:

  1. Bachelor’s, Master’s, PhD, or equivalent experience in Machine Learning, Computer Science, Maths, Data Science, or related fields.
  2. Proficiency in deep learning frameworks like PyTorch or JAX.
  3. Strong Python software development skills (knowledge of C++ or other languages is a plus).
  4. Familiarity with deep learning fundamentals such as models, optimisation, evaluation, and scaling.
  5. Experience in designing, executing, and reporting ML experiments.
  6. Ability to work quickly and effectively in a dynamic environment.
  7. Enjoy cross-functional collaboration with other teams.
  8. Strong communication skills, capable of explaining complex technical concepts to diverse audiences.
  9. Experience in one or more areas such as distributed training of large-scale ML models, building production systems with large language models, efficient computing with low-precision arithmetic, or large generative models for language, vision, and other modalities.
  10. Experience writing C++, Triton, or CUDA kernels for performance optimisation of ML models.
  11. Contributions to open-source projects or published research papers in relevant fields.
  12. Knowledge of cloud computing platforms.
  13. Keen to present, publish, and deliver talks in the AI community.

In addition to a competitive salary, Graphcore offers flexible working, a generous annual leave policy, private medical insurance, a health cash plan, dental plan, pension (matched up to 5%), life assurance, and income protection. We also provide a generous parental leave policy, an employee assistance programme (covering health, mental wellbeing, and bereavement support), healthy food and snacks at our Bristol office, and an on-site barista. We value diversity and are committed to creating an inclusive work environment. We offer flexible interview arrangements and reasonable adjustments upon request.

Applicants must have the right to work in the UK. We are currently unable to offer visa sponsorship or support.

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Machine Learning Engineer (Large Systems) employer: graphcore

Graphcore is an exceptional employer for Machine Learning Engineers, offering a dynamic work environment in Bristol where innovation thrives. With a strong focus on employee growth, we provide opportunities to collaborate with leading experts in AI, access to cutting-edge technology, and a comprehensive benefits package that includes flexible working arrangements, generous leave policies, and health support. Our commitment to diversity and inclusion ensures that every team member feels valued and empowered to make a meaningful impact in the rapidly evolving field of AI.
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Contact Detail:

graphcore Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Machine Learning Engineer (Large Systems)

✨Tip Number 1

Familiarise yourself with Graphcore's technology and products. Understanding their hardware and how it integrates with AI models will give you an edge in discussions during interviews, showcasing your genuine interest in the company.

✨Tip Number 2

Engage with the AI community by attending conferences, webinars, or meetups. Networking with professionals in the field can provide insights into the latest trends and may even lead to referrals for the position.

✨Tip Number 3

Prepare to discuss your experience with deep learning frameworks like PyTorch or JAX. Be ready to share specific examples of projects where you've implemented and optimised machine learning models, as this will demonstrate your hands-on expertise.

✨Tip Number 4

Showcase your collaborative skills by highlighting past experiences where you've worked cross-functionally. Emphasising your ability to communicate complex technical concepts to diverse teams will resonate well with Graphcore's emphasis on teamwork.

We think you need these skills to ace Machine Learning Engineer (Large Systems)

Proficiency in deep learning frameworks (e.g., PyTorch, JAX)
Strong Python software development skills
Knowledge of C++ or other programming languages
Understanding of deep learning fundamentals (models, optimisation, evaluation, scaling)
Experience in designing and executing ML experiments
Ability to work effectively in a dynamic environment
Cross-functional collaboration skills
Strong communication skills for explaining technical concepts
Experience in distributed training of large-scale ML models
Building production systems with large language models
Efficient computing with low-precision arithmetic
Experience with large generative models for various modalities
Writing C++, Triton, or CUDA kernels for performance optimisation
Contributions to open-source projects or published research papers
Knowledge of cloud computing platforms
Interest in presenting and publishing in the AI community

Some tips for your application 🫡

Tailor Your CV: Make sure your CV highlights relevant experience in machine learning, particularly with frameworks like PyTorch or JAX. Emphasise any projects where you've implemented or optimised AI models, as this aligns closely with the role.

Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for advancing AI technology and detail how your skills and experiences make you a perfect fit for the Machine Learning Engineer position at Graphcore. Mention specific projects or achievements that demonstrate your capabilities.

Showcase Collaboration Skills: Since the role involves working closely with various teams, highlight your experience in cross-functional collaboration. Provide examples of how you've successfully worked with software development or research teams in the past.

Demonstrate Continuous Learning: Mention any recent courses, certifications, or contributions to the AI community that showcase your commitment to staying updated with the latest developments in AI. This could include open-source contributions or published research papers.

How to prepare for a job interview at graphcore

✨Showcase Your Technical Skills

Be prepared to discuss your experience with deep learning frameworks like PyTorch or JAX. Highlight specific projects where you've implemented and optimised machine learning models, as this will demonstrate your technical proficiency.

✨Understand Graphcore's Technology

Research Graphcore's hardware and how it integrates with AI models. Being knowledgeable about their technology will allow you to ask insightful questions and show your genuine interest in the role.

✨Prepare for Collaborative Scenarios

Since the role involves cross-functional collaboration, think of examples where you've successfully worked with other teams. Be ready to discuss how you communicate complex technical concepts to diverse audiences.

✨Stay Updated on AI Developments

Engage with the latest trends and advancements in AI. Mention any recent papers or technologies that excite you, as this shows your passion for the field and your commitment to continuous learning.

Machine Learning Engineer (Large Systems)
graphcore
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  • Machine Learning Engineer (Large Systems)

    London
    Full-Time
    36000 - 60000 £ / year (est.)

    Application deadline: 2027-08-18

  • G

    graphcore

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