At a Glance
- Tasks: Validate and benchmark ML systems for reliable AI performance.
- Company: Join Graphcore, a leader in AI compute innovation.
- Benefits: Enjoy unlimited leave, matched pension, and flexible work options.
- Other info: Inclusive culture with excellent career growth opportunities.
- Why this job: Make an impact on next-gen AI systems and collaborate with diverse teams.
- Qualifications: Strong ML experience and Python skills required.
The predicted salary is between 70000 - 90000 £ per year.
Validate the ML stack that turns accelerator hardware into trusted AI performance. This role sits where modern ML models meet Graphcore’s software and hardware stack. You will test, benchmark and validate complex systems before they reach customers. Your work will expose regressions, correctness issues and performance limits across frameworks, models and execution environments. You will help teams understand what is working, what is breaking and why. You will run open source models, build automated benchmarking pipelines and create targeted tests for low level ML behaviour. That includes numerical precision, quantisation, attention mechanisms, distributed execution and model subgraphs. This is a role for someone who wants to stay close to how AI systems really work. You will not design new models, but you will make them run reliably on ambitious infrastructure.
The team and culture
The ML QA team is where Graphcore’s ML software stack comes together for validation. Work spans unit tests, full model benchmarks, distributed workloads, simulators, emulators and hardware targets. Engineers are expected to take ownership, question assumptions and improve how testing is done. The team moves quickly, but decisions are grounded in evidence, benchmark data and technical discussion. You will work closely with software, infrastructure and hardware teams. Squads organise around priorities, with space for engineers to shape roadmaps and raise the quality bar.
What we’re looking for
- Strong experience in Machine Learning or ML‑adjacent software engineering roles.
- A solid grasp of neural networks, training, inference, numerical precision and performance trade‑offs.
- Hands‑on experience with PyTorch, TensorFlow, JAX, Triton or similar ML frameworks and tools.
- Strong Python skills for automation, experimentation, benchmarking and reporting.
- Experience designing, running and analysing ML benchmarks or model experiments.
- Confident debugging skills in Linux, with curiosity about model behaviour and system performance.
Benefits
- Unlimited annual leave
- Up to 5% matched pension
- Phantom equity – share in Graphcore’s success
- True flexibility in how and where you work
- Office spaces designed for collaboration
- Free food and an on‑site barista
- Health cash plan
- Income protection
- Life assurance
- Along with other benefits you can choose from (private medical insurance, dental plan etc)
Inclusion
We welcome people from all backgrounds and experiences and are committed to building an inclusive environment where everyone can do their best work. We’re an equal opportunity employer and recognise that everyone brings different strengths and perspectives. If you need any adjustments during the interview process, just let us know – we’re happy to support you.
Join the Team at Graphcore
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 brings together deep expertise to solve complex problems and deliver meaningful progress in AI compute. If you want to validate the systems behind next generation AI compute, we’d love to hear from you.
Staff Engineer (ML Engineer) New Cambridge, UK employer: graphcore
Graphcore is an exceptional employer located in Cambridge, UK, offering a dynamic work culture that fosters innovation and collaboration among its diverse teams. With benefits like unlimited annual leave, matched pension contributions, and opportunities for personal growth, employees are empowered to take ownership of their work while contributing to groundbreaking advancements in AI technology. The company's commitment to inclusivity ensures that every team member can thrive and make a meaningful impact in the rapidly evolving field of artificial intelligence.
StudySmarter Expert Advice🤫
We think this is how you could land Staff Engineer (ML Engineer) New Cambridge, UK
✨Join Local Tech Meetups
Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at graphcore or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!
✨Contribute to Open Source Projects
Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to graphcore.
✨Tap into Online Developer Communities
Don’t underestimate the power of online developer communities like GitHub, Stack Overflow, and even Reddit. Participate in discussions, share your projects, and build your visibility. We can often find opportunities through these channels that can lead to a full-time gig at companies like graphcore.
✨Explore Job Boards Specifically for Tech Roles
Keep your eyes peeled on job boards that focus on tech roles. Sites like TechCareers or Stack Overflow Jobs can often have listings for companies like graphcore that might not show up on broader job sites. Make it a habit to check these regularly, and don’t hesitate to apply directly through our website!
We think you need these skills to ace Staff Engineer (ML Engineer) New Cambridge, UK
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at graphcore.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at graphcore and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at graphcore
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If graphcore uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.