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Senior Machine Learning Engineer (Large Systems)

Graphcore

Skills

Required

  • Machine Learning
  • Python / C++
  • ML models
  • software development
  • ML experiments
  • Data Science
  • MLOps
  • Kubernetes-based clusters
  • distributed training

Preferred

  • deep learning
  • frameworks
  • PyTorch / JAX
  • model training
  • evaluation
  • Triton / CUDA
  • performance optimisation
  • HPC systems
  • networking

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.

We seek engineers with strong technical foundations who are curious and eager to understand and advance AI model implementation, at scale

Building production systems with large language models

Keen to present, publish and deliver talks in the AI community

About Graphcore

If you're excited about advancing the next generation of AI models on cutting-edge hardware, we’d love to hear from you!

Responsibilities

  • 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.
  • Well-developed understanding of performance bottlenecks and how to overcome them
  • Enjoy cross-functional work collaborating with other teams

Requirements

  • 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
  • Bachelor/Master's/PhD or equivalent experience in Machine Learning, Computer Science, Maths, Data Science, or related field
  • MLOps for Kubernetes-based clusters
  • Efficient computing based on low-precision arithmetic
  • Experience in distributed training or inference of ML models across 64+ accelerators

Preferred

  • Proficiency in deep learning frameworks like PyTorch/JAX
  • Expertise in hardware-accelerated deep learning from model training to optimisation and evaluation

Experience in one or more of

  • Experience writing C++/Triton/CUDA kernels for performance optimisation of ML models
  • 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

Every job at Graphcore