At a Glance
- Tasks: Benchmark and validate ML models, ensuring performance and reliability across various environments.
- Company: Join Graphcore, a leader in AI compute backed by SoftBank, shaping the future of technology.
- Benefits: Enjoy flexible working, generous leave, private health insurance, and a vibrant office culture.
- Other info: Inclusive workplace with excellent career growth opportunities and a focus on innovation.
- Why this job: Make a real impact in AI while collaborating with top experts in a dynamic environment.
- Qualifications: Experience in ML engineering, strong Python skills, and familiarity with major ML frameworks required.
The predicted salary is between 60000 - 80000 € per year.
About Graphcore
At Graphcore, we’re building the future of AI compute. We’re a team of semiconductor, software and AI experts, with deep experience in creating the complete AI compute stack - from silicon and software to infrastructure at datacentre scale. As part of the SoftBank Group, backed by significant long-term investment, we are delivering key technology into the fast-growing SoftBank AI ecosystem. To meet the vast and exciting AI opportunity, Graphcore is expanding its teams around the world. We are bringing together the brightest minds to solve the toughest problems, in a place where everyone has the opportunity to make an impact on the company, our products and the future of artificial intelligence.
Job Summary
Applicants for this role should have strong experience working with machine learning systems and frameworks, along with a solid understanding of core AI concepts and model behaviour. The role centres on testing, validating, and benchmarking a complex ML software stack, with a particular focus on performance, reliability, and correctness across modern AI workloads. The ideal candidate is an experienced ML engineer who understands how contemporary models are trained and executed, and who has hands-on experience debugging functional and performance issues in ML systems. This person will be comfortable working with industry-standard frameworks and state-of-the-art models, bringing them up on internal infrastructure, and collaborating closely with software and hardware teams in a technically demanding environment spanning ML frameworks, infrastructure, and AI accelerator hardware.
The Team
The ML QA team is composed of highly skilled software engineers with a strong focus on automation, software quality, and data-driven validation. The team works closely with industry-standard machine learning frameworks and models, contributing to upstream open-source projects and collaborating across the wider software organization. Operating in a fast-paced environment, the team plays a critical role in ensuring reliability, performance, and maintainability across the ML software stack, helping to deliver robust and high-quality products to customers.
Responsibilities and Duties
- Benchmark ML models and frameworks, analysing results to identify regressions, performance bottlenecks, and correctness issues.
- Work hands-on with industry-standard ML frameworks to validate functionality and performance across different execution environments.
- Build and maintain automated testing and benchmarking pipelines targeting simulators, emulators, and physical hardware.
- Collaborate closely with software teams to ensure adequate test coverage for new and existing features.
- Develop tooling and scripts (primarily in Python) to support testing, benchmarking, and functional reporting.
- Take ownership over aspects of our testing and infrastructure, owning the roadmap and driving innovation independently.
Candidate Profile
Essential:
- Experience working in Machine Learning or ML-adjacent engineering roles.
- Strong foundation in core AI and ML concepts (e.g. neural networks, training vs inference, numerical precision, performance trade-offs).
- Hands-on experience with one or more major ML frameworks such as PyTorch, TensorFlow, JAX, or similar.
- Strong proficiency in Python for ML workflows, experimentation, and automation.
- Experience designing, running, and analysing ML benchmarks or experiments.
- Experience working in Linux environments.
- Strong analytical and debugging skills, with the ability to reason about model behaviour and system performance.
- Bachelor/Master's/PhD or equivalent experience in Computer Science, Maths, Machine Learning, Data Science, or related field.
Desirable
- Experience with MLOps pipelines, model deployment, or production ML systems.
- Familiarity with performance analysis, profiling tools, or numerical accuracy validation.
- Exposure to distributed training or inference systems.
- Experience with hardware-accelerated ML, compilers, or system-level performance considerations.
- Familiarity with CI/CD systems used for ML workflows.
- Experience contributing to open-source ML frameworks or tooling.
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.
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.
Senior Engineer (ML Engineer) in Bristol employer: graphcore
Graphcore is an exceptional employer, offering a dynamic work environment in the heart of Bristol where innovation thrives. With a strong focus on employee growth, we provide ample opportunities for professional development alongside competitive benefits such as flexible working, generous leave policies, and comprehensive health plans. Our inclusive culture fosters collaboration among top-tier talent, ensuring that every team member can make a meaningful impact on the future of AI technology.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Engineer (ML Engineer) in Bristol
✨Tip Number 1
Network like a pro! Reach out to current employees at Graphcore on LinkedIn or other platforms. A friendly chat can give you insider info and maybe even a referral, which can really boost your chances.
✨Tip Number 2
Prepare for technical interviews by brushing up on your ML frameworks and concepts. Practice coding challenges in Python and be ready to discuss your past projects. We want to see your hands-on experience shine!
✨Tip Number 3
Showcase your passion for AI and ML during interviews. Talk about the latest trends, your favourite projects, or any contributions to open-source. This will help us see your enthusiasm and commitment to the field.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining the Graphcore team.
We think you need these skills to ace Senior Engineer (ML Engineer) in Bristol
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience with machine learning systems and frameworks. We want to see how your skills align with the role, so don’t be shy about showcasing your hands-on experience and any relevant projects you've worked on.
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 our team. We love seeing enthusiasm and a clear understanding of the role.
Showcase Your Technical Skills:When applying, make sure to mention your proficiency in Python and any major ML frameworks like PyTorch or TensorFlow. We’re looking for candidates who can hit the ground running, so highlight any relevant tools or technologies you’ve worked with.
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, it shows us you’re serious about joining our awesome team!
How to prepare for a job interview at graphcore
✨Know Your ML Frameworks
Make sure you’re well-versed in the major ML frameworks like PyTorch and TensorFlow. Brush up on your hands-on experience with these tools, as you'll likely be asked to discuss how you've used them in past projects or experiments.
✨Understand AI Concepts Inside Out
Familiarise yourself with core AI concepts such as neural networks, training vs inference, and performance trade-offs. Be prepared to explain these concepts clearly, as they are fundamental to the role and will likely come up during technical discussions.
✨Showcase Your Debugging Skills
Be ready to talk about specific instances where you’ve debugged functional or performance issues in ML systems. Highlight your analytical skills and how you reason about model behaviour, as this will demonstrate your problem-solving capabilities.
✨Prepare for Collaboration Questions
Since the role involves working closely with software and hardware teams, think of examples that showcase your collaborative spirit. Be prepared to discuss how you’ve contributed to team projects, especially in fast-paced environments, and how you ensure adequate test coverage.