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Graphcore is seeking a Senior AI Performance Engineer to analyze and optimize AI training and inference workloads across large-scale distributed systems. You will own complex performance investigations from problem definition through validation, turning profiling, benchmarking, and modeling results into actionable improvements for engineering teams.
In this role, you will design benchmarks, investigate system bottlenecks, and optimize distributed communication software across technologies such as MPI, NCCL, UCX, and RDMA. Your work will help Graphcore deliver efficient, reliable AI systems for large-scale data center deployment. You will have rare scope across hardware, software, networking, and system architecture.
You will join the System Engineering Performance team, which architects, evaluates, and optimizes high-performance infrastructure for large-scale data center deployments. The team works across the computing stack to understand real system behavior. Work moves through evidence, ownership, and clear technical judgment. You will define investigations, coordinate across teams, and validate impact with reliable performance data. Decisions are shaped through benchmarks, models, simulations, and practical engineering tradeoffs. The team values engineers who think big, act fast, take responsibility, speak up, and lead beyond their own area.
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:
- Strong experience profiling and optimizing AI, machine learning, or high-performance computing workloads
- Experience with distributed systems and communication libraries such as MPI, NCCL, UCX, or libfabric
- Strong C++ and Python skills, including reliable tools or performance-sensitive software
- Deep understanding of compute, memory, and communication behavior in large-scale systems
- Ability to own complex technical work and coordinate improvements across teams
- Familiarity with MLPerf, accelerated architectures, ML frameworks, or high-performance interconnects
The company welcomes transferable skills and diverse experiences, and welcomes engineers returning to the profession after a career break.
