Senior Machine Learning Engineer (Large Systems) in London
Senior Machine Learning Engineer (Large Systems)

Senior Machine Learning Engineer (Large Systems) in London

London Full-Time 48000 - 72000 £ / year (est.) No home office possible
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At a Glance

  • Tasks: Develop and optimise AI models for cutting-edge hardware in a dynamic environment.
  • Company: Join Graphcore, a leader in AI innovation and part of the SoftBank Group.
  • Benefits: Enjoy flexible working, generous leave, private medical insurance, and a vibrant office culture.
  • Why this job: Make a tangible impact on the future of AI technology with a talented team.
  • Qualifications: Strong background in Machine Learning, Python/C++, and experience with deep learning frameworks.
  • Other info: Collaborate with diverse teams and engage with the AI community for continuous learning.

The predicted salary is between 48000 - 72000 £ per year.

About Graphcore

Graphcore is one of the world’s leading innovators in Artificial Intelligence compute. It is developing hardware, software and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry. As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone. Graphcore’s teams are drawn from diverse backgrounds and bring a broad range of skills and perspectives. A melting pot of AI research specialists, silicon designers, software engineers and systems architects, Graphcore enjoys a culture of continuous learning and constant innovation.

Job Summary

As a Senior 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. You will work on large scale systems where performance is critical to the success of our projects. Working closely with the Software development and Research teams, you will play a critical role in identifying opportunities to innovate and differentiate Graphcore’s technology. We seek engineers with strong technical skills and an understanding of AI model implementation at scale, 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 and at scale. 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 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 necessary 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

  • 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 or C++ software development skills.
  • Expertise in deep learning from model training to optimisation and evaluation.
  • Experience in distributed training or inference of ML models across 64+ accelerators.
  • Capable of designing, executing and reporting from ML experiments.
  • Developed deep understanding of performance bottlenecks and how to overcome them.
  • 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.

Desirable

  • Experience in one or more of:
  • MLOps for Kubernetes-based clusters.
  • Building production systems with large language models.
  • Efficient computing based on low-precision arithmetic.
  • Experience writing C++/Triton/CUDA kernels for performance optimisation of ML models.
  • Familiarity with HPC systems and networking including Infiniband, NVLink, RoCE technologies.
  • 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.

Benefits

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 offer a range of healthy food and snacks at our central Bristol office and have our own barista bar! 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.

Applicants for this position must hold the right to work in the UK. Unfortunately at this time, we are unable to provide visa sponsorship or support for visa applications.

Senior Machine Learning Engineer (Large Systems) in London employer: graphcore

Graphcore is an exceptional employer, offering a dynamic work culture that fosters continuous learning and innovation in the rapidly evolving field of AI. With a commitment to employee well-being, we provide flexible working arrangements, generous leave policies, and comprehensive health benefits, all within a collaborative environment that values diverse perspectives. Located in the vibrant city of Bristol, our team enjoys access to cutting-edge technology and the opportunity to make a tangible impact on the future of AI.
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Contact Detail:

graphcore Recruiting Team

StudySmarter Expert Advice 🤫

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

✨Tip Number 1

Network like a pro! Reach out to current employees at Graphcore on LinkedIn or other platforms. Ask them about their experiences and any tips they might have for landing a role in the Applied AI team.

✨Tip Number 2

Show off your skills! Prepare a portfolio of your machine learning projects, especially those that demonstrate your ability to optimise models for performance. This will give you an edge during interviews.

✨Tip Number 3

Stay updated with the latest in AI! Follow industry news, research papers, and trends. Being able to discuss recent advancements will show your passion and commitment to the field during interviews.

✨Tip Number 4

Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining the Graphcore team.

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

Machine Learning
Deep Learning Frameworks (PyTorch, JAX)
Python
C++
Model Training and Optimisation
Distributed Training
Performance Benchmarking
Experiment Design and Execution
Cross-Functional Collaboration
Communication Skills
MLOps for Kubernetes
Production Systems with Large Language Models
CUDA Kernels for Performance Optimisation
HPC Systems and Networking
Cloud Computing Platforms

Some tips for your application 🫡

Tailor Your CV: Make sure your CV is tailored to the Senior Machine Learning Engineer role. Highlight your experience with deep learning frameworks like PyTorch or JAX, and showcase any projects where you've optimised models for performance.

Craft a Compelling Cover Letter: Your cover letter should reflect your passion for AI and how your skills align with Graphcore's mission. Share specific examples of your work in large-scale systems and how you’ve tackled performance bottlenecks.

Showcase Collaboration Skills: Since this role involves working closely with various teams, emphasise your cross-functional collaboration experiences. Mention any successful projects where you’ve worked with software engineers or researchers to achieve common goals.

Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re keen on joining our team!

How to prepare for a job interview at graphcore

✨Know Your AI Models

Make sure you’re up to speed with the latest AI models and techniques relevant to the role. Brush up on your knowledge of deep learning frameworks like PyTorch or JAX, and be ready to discuss how you’ve implemented and optimised these models in past projects.

✨Showcase Your Problem-Solving Skills

Prepare to talk about specific challenges you've faced in optimising machine learning models, especially in large-scale systems. Be ready to explain how you identified performance bottlenecks and the strategies you used to overcome them.

✨Collaborate and Communicate

Since this role involves working closely with various teams, highlight your experience in cross-functional collaboration. Think of examples where you successfully communicated complex technical concepts to non-technical audiences, as this will show your ability to bridge gaps between teams.

✨Stay Current with Industry Trends

Engage with the AI community and keep abreast of the latest developments. Mention any conferences, papers, or open-source contributions you’ve been involved with. This shows your passion for the field and your commitment to continuous learning, which is key at Graphcore.

Senior Machine Learning Engineer (Large Systems) in London
graphcore
Location: London

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