Graphcore
AI Compute
SeniorEngineer(MLEngineer)
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optimal for Senior candidates.
“Senior Engineer (ML Engineer) at Graphcore. Skills: Machine Learning, ML Frameworks, Python, Benchmarking. Benchmark ML models and frameworks. Analyse results to identify regressions”
What You'll Achieve.
Ensure reliability; Ensure performance; Ensure maintainability; Deliver robust products; Deliver high-quality products
Industry & Context.
Analytical skills; Debugging skills; Reason about model behaviour; Reason about system performance
Must hold the right to work in the UK, Unable to provide visa sponsorship
What They're Looking For.
Must Have
Experience working in Machine Learning or ML-adjacent engineering roles, Foundation in core AI and ML concepts, Hands-on experience with one or more major ML frameworks such as PyTorch, TensorFlow, JAX, or similar, Proficiency in Python for ML workflows, experimentation, and automation, Experience designing, running, and analysing ML benchmarks or experiments, Experience working in Linux environments, Analytical and debugging skills, Bachelor/Master's/PhD or equivalent experience in Computer Science, Maths, Machine Learning, Data Science, or related field, Right to work in the UK
Nice to Have
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
What You'll Do.
Benchmark ML models and frameworks
Analyse results to identify regressions
Analyse results to identify performance bottlenecks
Analyse results to identify correctness issues
Work hands-on with ML frameworks
Validate functionality and performance
Build automated testing pipelines
Maintain automated testing pipelines
Build benchmarking pipelines
Maintain benchmarking pipelines
Develop tooling and scripts
Support functional reporting
Take ownership over testing aspects
Take ownership over infrastructure aspects
Drive innovation independently
How You'll Work.
Team & Collaboration
Collaborate closely with software teams; Collaborate with hardware teams; Collaborate across the wider software organization
Process & Methodology
Own the roadmap
Full Job Description
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 datacenter 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 environmen
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