Senior ML Engineer: Large-Scale AI Systems in Cambridge

Senior ML Engineer: Large-Scale AI Systems in Cambridge

Cambridge Full-Time 70000 - 90000 £ / year (est.) No working from home possible
graphcore

At a Glance

  • Tasks: Develop and optimise AI models for cutting-edge hardware in a dynamic environment.
  • Company: Join Graphcore, a leader in AI compute backed by SoftBank.
  • Benefits: Enjoy flexible working, generous leave, private medical insurance, and more.
  • Other info: Collaborate with top minds in AI and enjoy excellent career growth opportunities.
  • Why this job: Make a real impact on the future of AI technology with innovative projects.
  • Qualifications: Strong skills in machine learning, Python/C++, and deep learning frameworks required.

The predicted salary is between 70000 - 90000 £ per year.

Cambridge, UK

About Graphcore

At Graphcore, we’re building the future of AI compute. We’re a team of semiconductor, software and AI experts, with deep experience in creating the complete AI compute stack - from silicon and software to infrastructure at datacentre scale. As part of the SoftBank Group, backed by significant long-term investment, we are delivering key technology into the fast-growing SoftBank AI ecosystem. To meet the vast and exciting AI opportunity, Graphcore is expanding its teams around the world. We are bringing together the brightest minds to solve the toughest problems, in a place where everyone has the opportunity to make an impact on the company, our products and the future of artificial intelligence.

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.

Qualifications

  • 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.

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.

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 ML Engineer: Large-Scale AI Systems in Cambridge employer: graphcore

Graphcore is an exceptional employer, offering a dynamic work environment in Cambridge where innovation thrives. With a strong commitment to employee growth, we provide opportunities for professional development alongside competitive benefits such as flexible working, generous leave policies, and comprehensive health plans. Our inclusive culture fosters collaboration among talented individuals, making it an ideal place for those eager to make a significant impact in the rapidly evolving field of AI.

graphcore

Contact Details:

graphcore Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Senior ML Engineer: Large-Scale AI Systems in Cambridge

Tip Number 1

Network like a pro! Reach out to folks in the AI community, attend meetups, and connect with Graphcore employees on LinkedIn. A friendly chat can open doors that applications alone can't.

Tip Number 2

Show off your skills! If you’ve got projects or contributions to open-source work, make sure to highlight them. Share your GitHub or any relevant portfolio when you get the chance.

Tip Number 3

Prepare for those interviews! Brush up on your ML concepts and be ready to discuss how you’d tackle performance bottlenecks. Practice explaining complex ideas simply – it’ll impress the interviewers!

Tip Number 4

Don’t forget to 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 ML Engineer: Large-Scale AI Systems in Cambridge

Machine Learning
Deep Learning Frameworks (PyTorch, JAX)
Python
C++
Distributed Training
Performance Optimisation
MLOps for Kubernetes

Some tips for your application 🫡

Tailor Your Application:Make sure to customise your CV and cover letter for the Senior ML Engineer role. Highlight your experience with AI models, performance optimisation, and any relevant projects that showcase your skills in deep learning frameworks like PyTorch or JAX.

Showcase Your Technical Skills:Don’t hold back on your technical prowess! Include specific examples of your work with distributed training, model scaling, and any contributions to open-source projects. We want to see how you’ve tackled complex problems in the past.

Be Clear and Concise:When writing your application, keep it clear and to the point. Use straightforward language to explain your experiences and achievements. Remember, we’re looking for strong communicators who can convey complex ideas simply.

Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, you’ll find all the details about the role and our company culture there!

How to prepare for a job interview at graphcore

Know Your AI Models

Before the interview, 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, as well as any recent advancements in distributed training. This will show that you're not just technically skilled but also genuinely interested in the field.

Demonstrate Problem-Solving Skills

Prepare to discuss specific challenges you've faced in previous projects, especially those related to performance bottlenecks or model optimisation. Use the STAR method (Situation, Task, Action, Result) to structure your answers, making it easy for the interviewers to see how you approach complex problems.

Collaborative Mindset

Since the role involves working closely with various teams, be ready to share examples of successful cross-functional collaborations. Highlight how you’ve communicated complex technical concepts to non-technical stakeholders, as this will demonstrate your ability to work effectively within a team environment.

Ask Insightful Questions

At the end of the interview, don’t forget to ask questions! Inquire about Graphcore’s current projects, the technologies they’re excited about, or how they envision the future of AI. This shows your enthusiasm for the role and helps you gauge if the company is the right fit for you.