Graphcore
Staff Engineer (ML Engineer)
How your CV stacks up
Upload your CV to see how well it fits this job role
?%
Role: Machine Learning Quality Assurance Engineer
Location: Flexible About the Role
Validate the ML stack that turns accelerator hardware into trusted AI performance. This role sits at the intersection of modern ML models, Graphcore’s software, and hardware stack. Your focus will be on testing, benchmarking, and validating complex systems before they reach customers.
Key Responsibilities
- Identify and expose regressions, correctness issues, and performance limits across frameworks, models, and execution environments.
- Help teams analyse what is working, what is breaking, and why.
- Run open-source ML models, build automated benchmarking pipelines, and create targeted tests for:
- Numerical precision
- Quantisation
- Attention mechanisms
- Distributed execution
- Model subgraphs
- Ensure AI systems run reliably on ambitious infrastructure, without designing new models.
Team and Culture
Graphcore’s ML QA team is responsible for unifying and validating the ML software stack, spanning:
- Unit tests
- Full model benchmarks
- Distributed workloads
- Simulators
- Emulators
- Hardware testing
Reasons to use Rodeo
Start with a chat, not a search bar
Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
It searches the market for you
Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
Core Values:
✔ Ownership: Engineers take initiative, question assumptions, and improve testing methods. ✔ Speed with rigour: The team moves quickly, driven by evidence, benchmark data, and technical discussion. ✔ Collaboration: Close work across software, infrastructure, and hardware teams. ✔ Impact: Engineers help shape roadmaps and set quality standards.
Requirements
Strong experience in:
- Machine Learning or ML-adjacent software engineering.
- Neural networks (training, inference, numerical precision, and performance trade-offs).
- ML frameworks: PyTorch, TensorFlow, JAX, Triton, or similar.
Technical skills:
- Python proficiency for automation, experimentation, benchmarking, and reporting.
- Hands-on experience with designing, running, and analysing ML benchmarks/experiments.
- Confident debugger: Expertise in Linux systems, curiosity about Model behaviour and system performance.
Benefits
🍎 Unlimited annual leave 💰 Flexibility in how and where you work 🏢 Office spaces designed for collaboration 🍽️ Free food and on-site barista
Get help with your application
Your very own career expert that helps elevate your application to the next level.
✅ Financial benefits:
- Up to 5% matched pension.
- Phantom equity for sharing in Graphcore’s success.
- Health cash plan.
- Income protection & life assurance.
🌍 Diversity & inclusion: Graphcore welcomes candidates of all backgrounds. Equal opportunity employer; adjustments during the interview process are supported.
About Graphcore
Graphcore is a world-leading AI compute innovator, advancing hardware, software and systems infrastructure to accelerate AI breakthroughs. As part of the SoftBank Group, Graphcore partners with elite teams shaping transformative technologies, delivering AI Super Intelligence for global industries.
Joining Graphcore means contributing to the next era of AI efficiency. Apply now and help craft cutting-edge AI infrastructure.
Direct link: [Apply now]сной(attention to context in original language, potential typo أصغر in Arabic expansion) [to the full application].
“It took my CV and asked me questions relevant to understanding what kind of jobs to suggest for me. Suggestions were almost perfect. Jobs were exactly what I’ve been looking for.”
Jessica, London
Skills
Location