Senior Machine Learning Engineer (Large Systems)

Graphcore is a company building the future of AI compute, combining semiconductor, software, and AI expertise to create a complete AI compute stack from silicon to datacenter-scale infrastructure. It is part of the SoftBank Group and delivers technology into the SoftBank AI ecosystem. The company is expanding globally to address AI opportunities.

Essential:

• Bachelor/Master's/PhD or equivalent experience in Machine Learning, Computer Science, Maths, Data Science, or related field.
• Proficiency in deep learning frameworks like PyTorch and JAX.
• Strong Python or C++ software development skills.
• Expertise in deep learning from model training to optimisation and evaluation.
• Experience in distributed training or inference of ML models across 64+ accelerators.
• Capable of designing, executing and reporting from ML experiments.
• Developed deep understanding of performance bottlenecks and how to overcome them.
• Ability to move quickly in a dynamic environment.
• Enjoy cross-functional work collaborating with other teams.
• Strong communicator able to explain complex technical concepts to different audiences.

Desirable:

• Experience in one or more of: MLOps for Kubernetes-based clusters, building production systems with large language models, efficient computing based on low-precision arithmetic.
• Experience writing C++, Triton, CUDA kernels for performance optimisation of ML models.
• Familiarity with HPC systems and networking including Infiniband, NVLink, RoCE technologies.
• Contributions to open-source projects or published research papers in relevant fields.
• Knowledge of cloud computing platforms.
• Keen to present, publish and deliver talks in the AI community.

• Implement latest machine learning models and optimise them for performance and accuracy, scaling to thousands of accelerators.
• Test and evaluate new internal software releases, provide feedback to software engineering teams, make necessary code fixes, and conduct code reviews.
• Benchmark models and key ML techniques to identify performance bottlenecks and improve model efficiency.
• Design and conduct experiments on novel AI methods, implement them and evaluate results.
• Collaborate with Research, Software, and Product teams to define, build, and test Graphcore’s next generation of AI hardware.
• Engage with AI community and keep in touch with the latest developments in AI.