At a Glance
- Tasks: Develop and optimise AI models for cutting-edge hardware, collaborating with various teams.
- Company: Graphcore is at the forefront of AI technology, innovating with specialised hardware.
- Benefits: Enjoy flexible working, generous leave, private medical insurance, and healthy snacks.
- Why this job: Join a dynamic team pushing the boundaries of AI and make a real impact.
- Qualifications: Bachelor’s, Master’s, PhD in relevant fields; strong Python skills required.
- Other info: We value diversity and offer inclusive interview arrangements.
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., optimizing 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! Implement the 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 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 stay updated with the latest developments in AI. Bachelor’s, Master’s, PhD, or equivalent experience in Machine Learning, Computer Science, Maths, Data Science, or related fields. # Strong Python software development skills (knowledge of C++ or other languages is a plus). # Experience in designing, executing, and reporting ML experiments. # Experience in one or more areas such as distributed training of large-scale ML models, building production systems with large language models, efficient computing with low-precision arithmetic, or large generative models for language, vision, and other modalities. # Experience writing C++, Triton, or CUDA kernels for performance optimisation of ML models. # Contributions to open-source projects or published research papers in relevant fields. # 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, a health cash plan, dental plan, pension (matched up to 5%), life assurance, and income protection. We also provide a generous parental leave policy, an employee assistance programme (covering health, mental wellbeing, and bereavement support), healthy food and snacks at our Bristol office, and an on-site barista. We value diversity and are committed to creating an inclusive work environment. We offer flexible interview arrangements and reasonable adjustments upon request. indicates a required field Phone Have you added your full legal name and surname? * Do you have the legal right to work in the UK? * UK Demographic Data As part of our recruitment process, we ask for confidential diversity data from all applicants. This data will be anonymised for statistical purposes only and will not impact your application. We are only using this data to improve our hiring process to be inclusive of all backgrounds. Do you consider yourself to have a disability? * #
Machine Learning Engineer Language employer: Cerebras
Contact Detail:
Cerebras Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer Language
✨Tip Number 1
Familiarise yourself with Graphcore's technology and products. Understanding how their hardware works with AI models will give you an edge in discussions during interviews and show your genuine interest in the company.
✨Tip Number 2
Engage with the AI community by attending conferences, webinars, or meetups. Networking with professionals in the field can provide insights into the latest trends and may even lead to referrals for job openings.
✨Tip Number 3
Showcase your experience with relevant projects on platforms like GitHub. Highlighting your contributions to open-source projects or any published research can demonstrate your expertise and commitment to the field.
✨Tip Number 4
Prepare to discuss specific machine learning techniques and models you've worked with. Being able to articulate your hands-on experience with distributed training, model optimisation, or low-precision arithmetic will set you apart from other candidates.
We think you need these skills to ace Machine Learning Engineer Language
Some tips for your application 🫡
Understand the Role: Before applying, make sure you fully understand the responsibilities and requirements of the Machine Learning Engineer position at Graphcore. Familiarise yourself with their technology and the specific AI models they work with.
Tailor Your CV: Highlight your relevant experience in machine learning, software development, and any specific projects that align with Graphcore's focus. Emphasise your skills in Python, C++, and any contributions to open-source projects or research papers.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for AI and your eagerness to contribute to Graphcore’s mission. Mention specific experiences that demonstrate your ability to innovate and collaborate within teams.
Showcase Your Projects: If applicable, include links to your GitHub or portfolio where you have showcased your machine learning projects. This can provide tangible evidence of your skills and experience to the hiring team.
How to prepare for a job interview at Cerebras
✨Showcase Your Technical Skills
Make sure to highlight your strong Python development skills and any experience with C++ or other languages. Be prepared to discuss specific projects where you've implemented and optimised AI models, as this will demonstrate your technical expertise.
✨Understand the Company’s Technology
Familiarise yourself with Graphcore's hardware and how it integrates with AI models. Research their latest advancements and be ready to discuss how you can contribute to optimising AI models for their technology.
✨Prepare for Collaborative Scenarios
Since the role involves working closely with various teams, think of examples from your past experiences where you successfully collaborated on projects. Be ready to explain how you can engage with the Research, Software, and Product teams effectively.
✨Stay Updated with AI Developments
Engage with the AI community and keep abreast of the latest trends and technologies. Mention any relevant conferences, papers, or projects you've been involved in, as this shows your passion for the field and commitment to continuous learning.