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: Experience in machine learning, deep learning frameworks, and strong programming skills required.
- Other info: Collaborate with top minds in AI and contribute to groundbreaking advancements.
The predicted salary is between 54000 - 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.
If you're excited about advancing the next generation of AI models on cutting-edge hardware, we’d love to hear from you!
Responsibilities
- 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.
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) New London, UK employer: graphcore
Contact Detail:
graphcore Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Machine Learning Engineer (Large Systems) New London, UK
✨Tip Number 1
Network like a pro! Reach out to current employees at Graphcore on LinkedIn or attend industry events. A friendly chat can give you insider info and maybe even a referral!
✨Tip Number 2
Show off your skills! Prepare a portfolio of your projects, especially those related to AI and machine learning. Bring it along to interviews to demonstrate your hands-on experience.
✨Tip Number 3
Stay updated with the latest in AI tech. Follow relevant blogs, podcasts, and research papers. Being able to discuss recent advancements will impress your interviewers.
✨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) New London, 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, performance optimisation, and any relevant projects you've worked on. We want to see how your skills align with what we're looking for!
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 you can contribute to our mission. Be genuine and let your passion for AI and technology come through.
Showcase Your Projects: If you've worked on any interesting projects, especially those involving large-scale systems or deep learning frameworks like PyTorch or JAX, make sure to mention them. We love seeing practical examples of your work and how you've tackled challenges in the past.
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, it shows us that you're genuinely interested in joining our team at Graphcore!
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 will show that 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 gives a clear picture of your hands-on experience and problem-solving skills.
✨Collaboration is Key
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 worked with software engineers or researchers to achieve common goals, as this will demonstrate your ability to communicate complex ideas effectively.
✨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 your commitment to continuous learning, which is crucial for a role at Graphcore.