At a Glance
- Tasks: Develop and optimise AI models for cutting-edge hardware in a dynamic team environment.
- Company: Join Graphcore, a leader in AI technology innovation, shaping the future of machine learning.
- Benefits: Enjoy flexible working, generous leave, private medical insurance, and healthy snacks at the office.
- Why this job: Make a tangible impact in AI while collaborating with top experts in a vibrant culture.
- Qualifications: Bachelor's or higher in relevant fields; strong skills in Python and deep learning frameworks required.
- Other info: Diversity is valued; flexible interview arrangements available.
The predicted salary is between 43200 - 72000 Β£ 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 Graphcores 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.
Is this the role you are looking for If so read on for more details, and make sure to apply today.
The Team
The Applied AI teams role is to be proxies for our customers; we need to understand the latest AI models, applications, and software to ensure that Graphcores 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\βre excited about advancing the next generation of AI models on cutting-edge hardware, wed love to hear from you!
Responsibilities and Duties
- 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 Graphcores next generation of AI hardware.
- Engage with the AI community and stay updated with the latest developments in AI.
Candidate Profile
Essential skills:
- Bachelors, Masters, PhD, or equivalent experience in Machine Learning, Computer Science, Maths, Data Science, or related fields.
- Proficiency in deep learning frameworks like PyTorch or JAX.
- Strong Python software development skills (knowledge of C++ or other languages is a plus).
- Familiarity with deep learning fundamentals such as models, optimisation, evaluation, and scaling.
- Experience in designing, executing, and reporting ML experiments.
- Ability to work quickly and effectively in a dynamic environment.
- Enjoy cross-functional collaboration with other teams.
- Strong communication skills, capable of explaining complex technical concepts to diverse audiences.
- 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.
- 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, 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.
Applicants must have the right to work in the UK. We are currently unable to offer visa sponsorship or support.
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We take pride in our commitment to creating an inclusive and diverse workplace. 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. Your responses will remain confidential and will not be used in any way regarding your application. We are only using this data to improve our hiring process to be inclusive of all backgrounds.
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Machine Learning Engineer (London) employer: Cerebras
Contact Detail:
Cerebras Recruiting Team
StudySmarter Expert Advice π€«
We think this is how you could land Machine Learning Engineer (London)
β¨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 interviews, as you'll be able to discuss how your skills can directly contribute to their goals.
β¨Tip Number 2
Engage with the AI community by attending relevant meetups or conferences. Networking with professionals in the field can provide insights into current trends and may even lead to referrals for the position.
β¨Tip Number 3
Showcase your experience with deep learning frameworks like PyTorch or JAX through personal projects or contributions to open-source. Having tangible examples of your work can make a strong impression during discussions.
β¨Tip Number 4
Prepare to discuss your approach to optimising machine learning models. Be ready to share specific examples of challenges you've faced and how you overcame them, as this will demonstrate your problem-solving skills and technical expertise.
We think you need these skills to ace Machine Learning Engineer (London)
Some tips for your application π«‘
Tailor Your CV: Make sure your CV highlights relevant experience in machine learning, AI model implementation, and any specific frameworks like PyTorch or JAX. Use keywords from the job description to align your skills with what Graphcore is looking for.
Craft a Strong Cover Letter: In your cover letter, express your enthusiasm for the role and the company. Discuss how your background in machine learning and your collaborative skills make you a great fit for the Applied AI team at Graphcore.
Showcase Relevant Projects: If you've worked on projects involving distributed training, performance optimisation, or have contributed to open-source projects, be sure to mention these. Provide links or descriptions that demonstrate your hands-on experience.
Prepare for Technical Questions: Anticipate technical questions related to machine learning models, optimisation techniques, and your programming skills. Be ready to discuss your approach to problem-solving and any experiments you've conducted in the field.
How to prepare for a job interview at Cerebras
β¨Showcase Your Technical Skills
Make sure to highlight your proficiency in deep learning frameworks like PyTorch or JAX. Be prepared to discuss specific projects where you've implemented and optimised machine learning models, as this will demonstrate your hands-on experience.
β¨Understand Graphcore's Technology
Research Graphcore's hardware and how it integrates with AI models. Being knowledgeable about their technology will allow you to ask insightful questions and show your genuine interest in the role.
β¨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. This will illustrate your ability to work cross-functionally and communicate complex ideas effectively.
β¨Stay Updated on AI Trends
Engage with the latest developments in AI and be ready to discuss recent advancements or research that excites you. This shows your passion for the field and your commitment to continuous learning, which is crucial for a Machine Learning Engineer.