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 Group.
- Benefits: Enjoy flexible working, generous leave, private medical insurance, and more.
- Why this job: Make a tangible impact on the future of AI technology with innovative projects.
- Qualifications: Strong skills in machine learning, Python or C++, and experience with large-scale systems.
The predicted salary is between 70000 - 90000 £ per year.
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.
Responsibilities and Duties
- Implement latest machine learning models and optimise them for performance and accuracy, scaling to thousands 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’s/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.
Right to work in the UK (visa sponsorship not provided).
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) New Cambridge, UK employer: graphcore
Graphcore is an exceptional employer, offering a dynamic work environment in the heart of Cambridge where innovation thrives. With a strong commitment to employee growth, we provide opportunities for collaboration across teams and access to cutting-edge technology, all while promoting a healthy work-life balance through flexible working arrangements and comprehensive benefits. Our inclusive culture ensures that every team member can contribute meaningfully to the future of AI, making Graphcore not just a workplace, but a community dedicated to excellence.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Machine Learning Engineer (Large Systems) New Cambridge, UK
✨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 your application process. Personal connections can make a huge difference!
✨Tip Number 2
Prepare for technical interviews by brushing up on your coding skills and understanding of machine learning models. Practice common algorithms and be ready to discuss your past projects in detail. We want to see how you think and solve problems!
✨Tip Number 3
Show your passion for AI! Engage with the AI community by attending meetups, webinars, or conferences. Share your insights on social media or contribute to open-source projects. This not only builds your profile but also shows your commitment to the field.
✨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. Let’s get you that interview!
We think you need these skills to ace Senior Machine Learning Engineer (Large Systems) New Cambridge, UK
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 AI models, large systems, and any relevant projects that showcase your skills in optimising performance.
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're excited about working at Graphcore and how your background aligns with our mission to advance AI technology. Be genuine and let your passion show!
Showcase Your Technical Skills:Don’t forget to mention your proficiency in deep learning frameworks like PyTorch or JAX, and your experience with Python or C++. We want to see how you’ve tackled challenges in ML model implementation and optimisation.
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 Stuff
Make sure you brush up on the latest machine learning models and frameworks like PyTorch or JAX. Be ready to discuss your experience with optimising models for performance, especially in large-scale systems. This shows you're not just familiar with the theory but can apply it practically.
✨Showcase Your Projects
Prepare to talk about specific projects where you've implemented and optimised AI models. Highlight any challenges you faced, how you overcame them, and the impact your work had. This will demonstrate your problem-solving skills and ability to innovate.
✨Collaborate Like a Pro
Since the role involves working closely with various teams, be ready to discuss your experience in cross-functional collaboration. Share examples of how you've effectively communicated complex technical concepts to different audiences, as this is key in a dynamic environment.
✨Stay Current
Engage with the AI community and keep up with the latest developments. Mention any conferences you've attended, papers you've read, or contributions to open-source projects. This shows your passion for the field and commitment to continuous learning.