Senior Machine Learning Engineer (Large Systems)

Join Graphcore, a leading AI technology company, as a Senior Machine Learning Engineer. In this role, you will develop and optimize AI models for our specialized hardware, work on large-scale systems, and collaborate with various teams to innovate and differentiate our technology. You will also engage with the AI community and stay updated on the latest developments in the field. Enjoy a flexible work-life balance, private medical insurance, a pension plan, and opportunities for career progression and personal development.

• Contribuer au développement et à l'optimisation des modèles d'IA adaptés au matériel spécialisé de Graphcore.
• Travailler sur des systèmes à grande échelle où la performance est critique pour le succès des projets.
• Collaborer avec les équipes de recherche et de développement logiciel pour identifier les opportunités d'innovation.
• We seek engineers with strong technical skills and an understanding of AI model implementation at scale, eager to make a tangible impact in this rapidly evolving field
• Proficiency in deep learning frameworks like PyTorch/JAX
• Strong communicator - able to explain complex technical concepts to different audiences
• Ability to move quickly in a dynamic environment
• Expertise in deep learning from model training to optimisation and evaluation
• Capable of designing, executing and reporting from ML experiments
• Bachelor/Master's/PhD or equivalent experience in Machine Learning, Computer Science, Maths, Data Science, or related field
• Strong Python or C++ software development skills
• Enjoy cross-functional work collaborating with other teams
• Experience in distributed training or inference of ML models across 64+ accelerators
• Developed deep understanding of performance bottlenecks and how to overcome them
• Keen to present, publish and deliver talks in the AI community
• Have contributed to open-source projects or published research papers in relevant fields
• Experience writing C++/Triton/CUDA kernels for performance optimisation of ML models
• Knowledge of cloud computing platforms
• Familiarity with HPC systems and networking including Infiniband, NVLink, RoCE technologies
• MLOps for Kubernetes-based clusters
• Efficient computing based on low-precision arithmetic
• If you're excited about advancing the next generation of AI models on cutting-edge hardware, we’d love to hear from you!
• Building production systems with large language models