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

Machine Learning Engineer (Large Systems)

Bristol Full-Time 36000 - 60000 £ / year (est.) Home office (partial)
Go Premium
G

At a Glance

  • Tasks: Develop and optimise AI models for cutting-edge hardware in a dynamic team.
  • Company: Graphcore is at the forefront of AI technology, innovating with specialised hardware.
  • Benefits: Enjoy flexible working, generous leave, private medical insurance, and a supportive environment.
  • Why this job: Make a tangible impact in AI while collaborating with top experts in a vibrant culture.
  • Qualifications: Bachelor's/Master's/PhD in relevant fields; strong skills in Python and deep learning frameworks required.
  • Other info: We value diversity and inclusivity, offering a supportive workplace for all backgrounds.

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. optimising 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

  • Implement the latest machine learning models and optimise them for performance and accuracy, scaling to 1000s of accelerators.
  • Test and evaluate new internal software releases, provide feedback to software engineering teams, make vital code fixes, and conduct code reviews.
  • Benchmark models and key ML techniques to identify performance bottlenecks and improve model efficiency.
  • Design and conduct experiments on novel AI methods, implement them and evaluate results.
  • Collaborate with Research, Software, and Product teams to define, build, and test Graphcore’s next generation of AI hardware.
  • Engage with AI community and keep in touch with the latest developments in AI.

Candidate Profile

Essential skills:

  • Bachelor/Master\’s/PhD or equivalent experience in Machine Learning, Computer Science, Maths, Data Science, or related field.
  • Proficiency in deep learning frameworks like PyTorch/JAX.
  • Strong Python software development skills (nice to have C++/other languages).
  • Familiar with deep learning fundamentals: models, optimisation, evaluation and scaling.
  • Capable of designing, executing and reporting from ML experiments.
  • Ability to move quickly in a dynamic environment.
  • Enjoy cross-functional work collaborating with other teams.
  • Strong communicator – able to explain complex technical concepts to different audiences.
  • Experience in one or more of: distributed training of large-scale ML models, building production systems with large language models, efficient computing based on low-precision arithmetic, deep learning models including large generative models for language, vision and other modalities.
  • Experience writing C++/Triton/CUDA kernels for performance optimisation of ML models.
  • Have contributed to open-source projects or published research papers in relevant fields.
  • Knowledge of cloud computing platforms.
  • 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 and health cash plan, a dental plan, pension (matched up to 5%), life assurance and income protection. We have a generous parental leave policy and an employee assistance programme (which includes health, mental wellbeing, and bereavement support). We welcome people of different backgrounds and experiences; we’re committed to building an inclusive work environment that makes Graphcore a great home for everyone. We offer an equal opportunity process and understand that there are visible and invisible differences in all of us. We can provide a flexible approach to interview and encourage you to chat to us if you require any reasonable adjustments.

#J-18808-Ljbffr

Machine Learning Engineer (Large Systems) employer: graphcore

Graphcore is an exceptional employer for Machine Learning Engineers, offering a dynamic work environment where innovation thrives. With a strong commitment to employee growth, flexible working arrangements, and comprehensive benefits including private medical insurance and generous parental leave, Graphcore fosters a culture of inclusivity and collaboration. Join us in advancing AI technology on cutting-edge hardware while enjoying the support and resources needed to excel in your career.
G

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 a significant edge during discussions and interviews.

✨Tip Number 2

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

✨Tip Number 3

Showcase your experience with deep learning frameworks like PyTorch or JAX through personal projects or contributions to open-source. This practical demonstration of your skills can set you apart from other candidates.

✨Tip Number 4

Prepare to discuss your past experiences with distributed training and performance optimisation. Be ready to share specific examples of challenges you've faced and how you overcame them, as this will highlight your problem-solving abilities.

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
Familiarity with C++ or other programming languages
Understanding of deep learning fundamentals (models, optimisation, evaluation, scaling)
Experience in designing and executing ML experiments
Ability to benchmark models and identify performance bottlenecks
Knowledge of distributed training of large-scale ML models
Experience with efficient computing using low-precision arithmetic
Familiarity with building production systems with large language models
Experience writing C++/Triton/CUDA kernels for performance optimisation
Knowledge of cloud computing platforms
Strong communication skills for explaining complex technical concepts
Experience contributing to open-source projects or publishing research papers
Ability to work collaboratively in cross-functional teams
Adaptability to a dynamic work environment
Engagement with the AI community and staying updated on latest developments

Some tips for your application 🫡

Understand the Role: Before applying, make sure you fully understand the responsibilities and requirements of the Machine Learning Engineer position at Graphcore. Familiarise yourself with their technology and the specific skills they are looking for.

Tailor Your CV: Customise your CV to highlight relevant experience in machine learning, software development, and any specific frameworks like PyTorch or JAX. Emphasise your contributions to projects, especially those involving large-scale models or performance optimisation.

Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for AI and your understanding of Graphcore's mission. Mention specific projects or experiences that align with the role and demonstrate your ability to innovate within the AI ecosystem.

Showcase Your Communication Skills: Since strong communication is essential for this role, ensure your application reflects your ability to explain complex concepts clearly. Consider including examples of how you've successfully communicated technical ideas to diverse audiences.

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 and relevance to the role.

✨Understand Graphcore's Technology

Research Graphcore’s hardware and how it integrates with AI models. Being able to articulate how your skills can enhance their technology will show your genuine interest in the company and its mission.

✨Prepare for Collaborative Scenarios

Since the role involves cross-functional work, think of examples where you've successfully collaborated with other teams. Be ready to discuss how you communicate complex technical concepts to non-technical 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
Go Premium

Land your dream job quicker with Premium

You’re marked as a top applicant with our partner companies
Individual CV and cover letter feedback including tailoring to specific job roles
Be among the first applications for new jobs with our AI application
1:1 support and career advice from our career coaches
Go Premium

Money-back if you don't land a job in 6-months

G
  • Machine Learning Engineer (Large Systems)

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

    Application deadline: 2027-08-18

  • G

    graphcore

Similar positions in other companies
UK’s top job board for Gen Z
discover-jobs-cta
Discover now
>