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Graphcore is seeking a Principal AI Performance Engineer to define how the company analyzes and optimizes AI training and inference workloads at data center scale. You will lead the hardest performance investigations, from model behavior to multi-node scaling, and turn profiling, benchmarking, and modeling evidence into technical roadmaps and engineering priorities.
You will set measurement standards across the organization, guide distributed communication strategy, and review critical C++ and Python tools. Your judgment will help teams make better decisions when data is incomplete. This role gives you rare influence across AI infrastructure at data center scale, working within the System Engineering Performance team that architects, evaluates, and optimizes high-performance infrastructure for large-scale deployments.
Work happens through evidence, technical ownership, and direct cross-team influence. You will guide strategy, resolve complex tradeoffs, and raise performance-engineering standards across the organization. The team values engineers who think big, act fast, take responsibility, speak up, and lead beyond their own area. Decisions are shaped by benchmarks, simulations, models, and clear technical debate.
Graphcore is one of the world's leading innovators in AI compute, developing hardware, software, and systems infrastructure to unlock the next generation of AI breakthroughs. As part of the SoftBank Group, Graphcore is positioned to drive transformative progress in AI compute.
REQUIREMENTS:
• Deep experience profiling and optimizing AI, machine learning, or high-performance computing workloads at scale
• Proven technical leadership across complex performance-engineering or system-architecture initiatives
• Expert C++ and Python skills, including reliable tools or performance-sensitive software
• Expert understanding of compute, memory, communication, and scaling behavior in distributed systems
• Ability to define benchmarks, measurement practices, or optimization standards across teams
• Experience with MPI, NCCL, UCX, libfabric, MLPerf, accelerated architectures, or high-performance interconnects
The company welcomes transferable skills and diverse experiences, and is open to engineers returning to the profession after a career break.
