2026 Graduate Machine Learning Engineer - Applied AI in Bristol
2026 Graduate Machine Learning Engineer - Applied AI

2026 Graduate Machine Learning Engineer - Applied AI in Bristol

Bristol Full-Time 36000 - 60000 ÂŁ / year (est.) No home office possible
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At a Glance

  • Tasks: Develop and optimise AI models for cutting-edge hardware in a collaborative environment.
  • Company: Join Graphcore, a leader in AI innovation and part of the SoftBank Group.
  • Benefits: Enjoy flexible working, competitive salary, generous leave, and health benefits.
  • Why this job: Make a real impact in AI technology and push boundaries with your skills.
  • Qualifications: Degree in Machine Learning or related field; proficiency in deep learning frameworks.
  • Other info: Be part of an inclusive culture that values diverse backgrounds and experiences.

The predicted salary is between 36000 - 60000 ÂŁ per year.

About Us

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 Graduate 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 identifying opportunities to innovate and differentiate Graphcore’s technology. This role is ideal for someone who loves working hands‑on with models, has a strong foundation in ML fundamentals, and wants to push the boundaries of AI performance in real‑world systems.

The Team

The Applied AI team’s role is 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 different modalities and applications.

Responsibilities And Duties

  • Implement state‑of‑the‑art machine learning models and optimise them for performance and accuracy, scaling to thousands of accelerators.
  • Evaluate new software releases, provide feedback to software engineering teams, make necessary code fixes, and conduct code reviews.
  • Benchmark models and key model components to identify performance bottlenecks and improve model efficiency.
  • Design and conduct experiments on novel AI methods, analyse and report results clearly.
  • Collaborate with Research, Software, and Product teams to define, build, and test Graphcore’s next generation of AI hardware.
  • Stay current with AI research and actively engage with the broader AI and open‑source community.

Candidate Profile

Essential

  • Bachelor’s/Master's degree in Machine Learning, Computer Science, Maths, Data Science, or related field.
  • Proficiency in deep learning frameworks such as PyTorch/JAX and strong software development skills.
  • Solid understanding of deep learning fundamentals — architectures, optimisation, evaluation, and scaling.
  • Capable of designing, executing and reporting from ML experiments.
  • Comfortable working in a fast‑moving, occasionally ambiguous environment.
  • Enjoy cross‑functional work collaborating with other teams.

Desirable

  • Development of deep learning models including large generative models for language, vision and other modalities.
  • Low‑precision/efficient compute.
  • Distributed training of large‑scale ML models.
  • Experience writing high performance C++/Triton/CUDA kernels.
  • Contributions to open‑source projects or published research.
  • Familiarity with cloud platforms and ML infrastructure.
  • Enthusiasm for presenting, publishing, or engaging 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.

Seniority level: Internship

Employment type: Full‑time

Job function: Engineering and Information Technology

Industries: Semiconductor Manufacturing

2026 Graduate Machine Learning Engineer - Applied AI in Bristol employer: graphcore

Graphcore is an exceptional employer, offering a dynamic and inclusive work culture that fosters continuous learning and innovation in the field of Artificial Intelligence. Located in the vibrant city of Bristol, employees benefit from flexible working arrangements, generous leave policies, and comprehensive health plans, all while collaborating with a diverse team of experts dedicated to pushing the boundaries of AI technology. With ample opportunities for professional growth and engagement in the broader AI community, Graphcore is committed to ensuring that every team member can thrive both personally and professionally.
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Contact Detail:

graphcore Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land 2026 Graduate Machine Learning Engineer - Applied AI in Bristol

✨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 might just get your foot in the door.

✨Tip Number 2

Show off your skills! If you’ve got projects or contributions to open-source that relate to AI, make sure to highlight them. Create a portfolio or GitHub repo to showcase your work and share it during interviews.

✨Tip Number 3

Prepare for technical interviews by brushing up on your ML fundamentals. Practice coding challenges and be ready to discuss your thought process. We want to see how you tackle problems, so think aloud!

✨Tip Number 4

Don’t forget to 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.

We think you need these skills to ace 2026 Graduate Machine Learning Engineer - Applied AI in Bristol

Machine Learning Fundamentals
Deep Learning Frameworks (PyTorch, JAX)
Software Development Skills
Model Optimisation
Performance Benchmarking
Experiment Design and Execution
Collaboration with Cross-Functional Teams
Distributed Training of ML Models
C++/Triton/CUDA Programming
Cloud Platforms Familiarity
Open-Source Contributions
Strong Analytical Skills
Effective Communication Skills
Adaptability in Fast-Paced Environments

Some tips for your application 🫡

Tailor Your CV: Make sure your CV reflects the skills and experiences that align with the Graduate Machine Learning Engineer role. Highlight your proficiency in deep learning frameworks and any relevant projects you've worked on. We want to see how you can contribute to our team!

Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about AI and how your background makes you a great fit for Graphcore. Don’t forget to mention any hands-on experience with ML models or collaboration with cross-functional teams.

Showcase Your Projects: If you've worked on any interesting AI projects, make sure to include them in your application. Whether it's a personal project or something from your studies, we love seeing practical applications of your skills. It gives us insight into your problem-solving abilities!

Apply Through Our Website: We encourage you to apply directly through our website. This ensures your application gets to the right people quickly. Plus, it’s super easy! Just follow the prompts and let us know why you’re excited about joining the Graphcore family.

How to prepare for a job interview at graphcore

✨Know Your ML Fundamentals

Brush up on your machine learning fundamentals, especially deep learning architectures and optimisation techniques. Be ready to discuss how these concepts apply to real-world scenarios, as Graphcore values practical knowledge in their innovative environment.

✨Familiarise with Graphcore's Technology

Take some time to understand Graphcore's hardware and software offerings. Knowing how their technology differentiates itself in the AI landscape will help you articulate how you can contribute to their mission during the interview.

✨Prepare for Hands-On Problem Solving

Expect to tackle hands-on coding challenges or case studies related to optimising AI models. Practise coding in frameworks like PyTorch or JAX, and be prepared to explain your thought process clearly while solving problems.

✨Engage with the AI Community

Show your enthusiasm for AI by discussing any contributions you've made to open-source projects or relevant research. This demonstrates your commitment to continuous learning and innovation, which aligns with Graphcore's culture.

2026 Graduate Machine Learning Engineer - Applied AI in Bristol
graphcore
Location: Bristol

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