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 and collaborate with top experts.
- Qualifications: Experience in machine learning, deep learning frameworks, and strong programming skills required.
- Other info: Inclusive workplace committed to diverse backgrounds and continuous learning.
The predicted salary is between 43200 - 72000 ÂŁ per year.
Bristol, UK; Cambridge, UK; London, UK
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 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.
- 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.
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Senior Machine Learning Engineer (Large Systems) employer: graphcore
Contact Detail:
graphcore Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Machine Learning Engineer (Large Systems)
✨Tip Number 1
Network like a pro! Reach out to folks in the AI community, attend meetups, and connect with Graphcore employees on LinkedIn. Building relationships can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects, especially those optimised for large systems. This will give you an edge and demonstrate your hands-on experience.
✨Tip Number 3
Prepare for technical interviews by brushing up on your deep learning frameworks and coding skills. Practice explaining complex concepts simply, as communication is key in cross-functional teams.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you're genuinely interested in joining the Graphcore team and contributing to our mission.
We think you need these skills to ace Senior Machine Learning Engineer (Large Systems)
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 innovation 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, you'll find all the details you need about the role and our company culture there!
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 how you've implemented and optimised these models in the past, especially in large-scale systems.
✨Showcase Your Collaboration Skills
Graphcore values teamwork, so be prepared to share examples of how you've worked cross-functionally with software engineers and researchers. Highlight any projects where you’ve collaborated to solve complex problems or improve AI performance.
✨Demonstrate Your Problem-Solving Abilities
Think of specific instances where you identified performance bottlenecks in ML models and how you overcame them. Discuss your approach to designing and conducting experiments, as well as how you evaluated the results.
✨Engage with the AI Community
Show your passion for AI by mentioning any contributions to open-source projects or research papers you've published. If you've presented at conferences or delivered talks, bring that up too—it shows you're active in the field!