Graphcore
AI Compute
StaffEngineer(MLEngineer)
Neural analysis suggests this role is
optimal for Staff candidates.
“Staff Engineer (ML Engineer) at Graphcore. Skills: Machine Learning, ML frameworks, Python, Benchmarking. Benchmark ML models. analyse results”
What You'll Achieve.
ensure reliability, performance, and maintainability; deliver robust and high-quality products
Industry & Context.
analytical and debugging skills; reason about model behaviour and system performance
hold the right to work in the UK, unable to provide visa sponsorship
What They're Looking For.
Must Have
Machine Learning or ML-adjacent engineering roles, core AI and ML concepts, PyTorch, TensorFlow, JAX, or similar, Python for ML workflows, experimentation, and automation, designing, running, and analysing ML benchmarks or experiments, Linux environments, analytical and debugging skills, 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
Nice to Have
MLOps pipelines, model deployment, or production ML systems, performance analysis, profiling tools, or numerical accuracy validation, distributed training or inference systems, hardware-accelerated ML, compilers, or system-level performance considerations, CI/CD systems used for ML workflows, contributing to open-source ML frameworks or tooling
What You'll Do.
identify performance bottlenecks
identify correctness issues
validate functionality and performance
Build automated testing pipelines
maintain automated testing pipelines
support functional reporting
Take ownership over testing
Take ownership over infrastructure
driving innovation independently
How You'll Work.
Team & Collaboration
collaborating closely with software and hardware teams; collaborating across the wider software organization
Process & Methodology
owning 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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