Graphcore
Senior Engineer (ML Engineer)
How your CV stacks up
Upload your CV to see how well it fits this job role
?%
Senior Engineer (ML Engineer)
Job Title: Machine Learning Throughput Validator (ML Test Engineer)
About 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.
About the Role
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.
- Expose regressions, correctness issues and performance limits across frameworks, modules and execution environments.
- Help teams understand what works, what breaks, and why.
- Run open-source models, build automated benchmarking pipelines and create targeted tests covering:
- Numerical precision
- Quantisation
- Attention mechanisms
- Distributed execution
- Model subgraphs
This role is for someone who thrives at the intersection of how AI systems work—you won’t design models, but you’ll ensure they run reliably on cutting-edge hardware.
The Team & Culture
The ML QA (Quality Assurance) team is where Graphcore’s ML software stack comes together for validation.
Your work spans:
- Unit tests
- Full model benchmarks
- Distributed workloads, simulators, and hardware targets
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.
Key Mindsets:
✔ Take ownership – Drive technical improvements beyond basic QA. ✔ Question assumptions – Base decisions on evidence, benchmarks and discussion, not dogma. ✔ ** Köllektion** – Move quickly, but with rigorous technical reasoning.
You’ll collaborate closely with software, infrastructure and hardware teams. The squad structure ensures flexible ownership—you’ll shape priorities and raise quality standards.
What We’re Looking For
This role demands global, ML-specialised expertise with a devops pioneering mindset.
Core Technical Requirements
- Functional or software engineering experience by default.
Key Skills
- Machine Learning proficiency – Strong grasp of neural networks, training, inference, numerical precision, performance and foundational AI mechanisms.
- Hardware awareness – Understanding of accelerator hardware, memory hierarchies, andAI systems stress and limitations.
- ML frameworks – Hands on experience with: PyTorch, TensorFlow, JAX, Triton or similar*.
- Python mastery – Scripting and benchmarking, pipeline automation and data-driven reporting.
- Benchmarking error-hunting experience – Running open-source ML models; designing targeted proof-of-concept tests.
- Debugging superpowers – Proficient in Linux systems, filled with curiosity about model classification, execution flow and numerical detail.
Key Examples of Daily Impact
Your work pushes toward delivering AI models on Graphcore hardware. Examples of technically deep impact targets include:
- Ensuring tensor operations behaving correctly under precision/quantization.
- Interימת data flows through hardware emulation.
- Identifying bottlenecks in flow bottlenecks across accelerated workloads.
Get help with your application
Your very own career expert that helps elevate your application to the next level.
Who Should Apply?
- How important are systems to you? This role rewards involvement and deep testing.
- Unloveable data? Solve puzzles with rigor! The cloud operates on highest complexity.
Benefits at Graphcore
Flexibility & Pension: 💰
- Unlimited annual leave
- Up to 5% matched pension
Equity & Growth: 🌱
- Phantom equity – share in Graphcore’s prestigious success.
Work-Life Balance: ☕🍽️
- Full flexibility in workspace or remote options.
- Vibrant London-based office designed for collaboration.
- Free food and dedicated on-site barista.
Health & Wellbeing: 💙
- Health cash plan
- Income protection
- Life assurance
- Plus choice-based extras such as private medical, dental, and wellness schemes. A range of additional perks builds years of stability.
Graphcore’s Commitment to Diversity
We welcome applicants from all backgrounds and are committed to building an environment that empowers everyone’s best potential.
- Equal opportunity employer – diversity strengthens our quest to solve AIեռinterest problems.
- Need adjustments during the process? Simple: just ask us.
Join Us
Graphcore isn’t just another tech creator—it’s the reluctant designer of a new era for AI workloads.
If you are proud of many a bug-bust, or deeply nurture how models optimize at the edge of tomorrow – apply, and build Graphcore’s next milestone.
“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