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 specialized hardware, work on large-scale systems, and collaborate with researchers in the field. You will have the opportunity to innovate and differentiate Graphcore's technology while enjoying a flexible hybrid working model and a range of benefits.

- Contribuer au développement et à l'optimisation de nouveaux modèles d'IA pour le matériel spécialisé. - Travailler sur des systèmes à grande échelle où la performance est critique pour le succès des projets. - Collaborer avec les équipes de recherche, de logiciels et de produits pour définir, construire et tester la prochaine génération de matériel d'IA de Graphcore.

- We seek engineers with strong technical foundations who are curious and eager to understand and advance AI model implementation, at scale - If you're excited about advancing the next generation of AI models on cutting-edge hardware, we’d love to hear from you! - Strong communicator - able to explain complex technical concepts to different audiences - Strong Python or C++ software development skills - Ability to move quickly in a fast-moving field - Capable of designing, executing and reporting from ML experiments - Well-developed understanding of performance bottlenecks and how to overcome them - 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/JAX - Enjoy cross-functional work collaborating with other teams - Expertise in hardware-accelerated deep learning from model training to optimisation and evaluation - 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 - Experience in distributed training or inference of ML models across 64+ accelerators - Familiarity with HPC systems and networking including Infiniband, NVLink, RoCE technologies, and cloud computing platforms - Have contributed to open-source projects or published research papers in relevant fields - Keen to present, publish and deliver talks in the AI community