At a Glance
- Tasks: Develop and optimise AI models for cutting-edge hardware in a dynamic team.
- Company: Join Graphcore, a leader in AI technology innovation and development.
- Benefits: Enjoy flexible working, generous leave, private medical insurance, and more perks.
- Why this job: Make a tangible impact in AI while collaborating with top experts in the field.
- Qualifications: Bachelor's/Master's/PhD in relevant fields; strong skills in Python and deep learning frameworks.
- Other info: Open to diverse backgrounds; commitment to an inclusive work environment.
The predicted salary is between 36000 - 60000 £ per year.
As a 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. Working closely with the Software development and Research teams, you will play a critical role in finding opportunities to innovate and differentiate Graphcore’s technology. We seek engineers with strong technical skills and an understanding of AI model implementation, eager to make a tangible impact in this rapidly evolving field.
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. 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 the 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 vital 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 the AI community and keep in touch with the latest developments in AI.
Essential skills:
- 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 software development skills (nice to have C++/other languages).
- Familiar with deep learning fundamentals: models, optimisation, evaluation and scaling.
- Capable of designing, executing and reporting from ML experiments.
- 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: distributed training of large-scale ML models, building production systems with large language models, efficient computing based on low-precision arithmetic, deep learning models including large generative models for language, vision and other modalities.
- Experience writing C++/Triton/CUDA kernels for performance optimisation of ML models.
- 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 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.
Application RequirementsApplicants 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.
Machine Learning Engineer employer: graphcore
Contact Detail:
graphcore Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer
✨Tip Number 1
Familiarise yourself with Graphcore's technology and products. Understanding how their hardware interacts with AI models will give you an edge in discussions during interviews, showcasing your genuine interest in their work.
✨Tip Number 2
Engage with the AI community by attending relevant conferences or meetups. Networking with professionals in the field can provide insights into the latest trends and may even lead to referrals for the position.
✨Tip Number 3
Brush up on your Python and deep learning frameworks like PyTorch or JAX. Being able to demonstrate your coding skills through practical examples or projects can significantly boost your chances during technical interviews.
✨Tip Number 4
Prepare to discuss your experience with distributed training and model optimisation. Be ready to share specific examples of challenges you've faced and how you overcame them, as this aligns closely with the responsibilities of the role.
We think you need these skills to ace Machine Learning Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in machine learning, software development, and any specific projects that demonstrate your skills with frameworks like PyTorch or JAX. Use keywords from the job description to align your experience with what Graphcore is looking for.
Craft a Strong Cover Letter: In your cover letter, express your enthusiasm for AI technology and how your background makes you a great fit for the Applied AI team. Mention specific experiences where you've implemented or optimised AI models, and how you can contribute to Graphcore's innovative projects.
Showcase Your Projects: If you have contributed to open-source projects or published research papers, include these in your application. Highlight any relevant projects that demonstrate your ability to work with large-scale ML models or efficient computing techniques.
Prepare for Technical Questions: Be ready to discuss your technical skills in detail during the interview process. Brush up on deep learning fundamentals, model optimisation, and your experience with distributed training. Prepare examples of how you've solved complex problems in previous roles.
How to prepare for a job interview at graphcore
✨Showcase Your Technical Skills
Be prepared to discuss your experience with deep learning frameworks like PyTorch or JAX. Highlight specific projects where you've implemented and optimised machine learning models, as this will demonstrate your technical proficiency.
✨Understand Graphcore's Technology
Research Graphcore's hardware and how it integrates with AI models. Being able to articulate how your skills can contribute to their technology will show your genuine interest in the role and the company.
✨Prepare for Problem-Solving Questions
Expect to face questions that assess your problem-solving abilities, especially related to performance bottlenecks and model efficiency. Practice explaining your thought process clearly and concisely.
✨Demonstrate Collaboration Skills
Since the role involves working closely with various teams, be ready to share examples of past collaborative projects. Emphasise your communication skills and ability to explain complex concepts to different audiences.