Description
As a Principal AI Performance Engineer, you will define how Graphcore analyzes and optimizes AI training and inference workloads. Your work will shape decisions across hardware, software, networking and system architecture. You will lead the hardest performance investigations, from model behavior to multi-node scaling. You will turn profiling, benchmarking and modeling evidence into technical roadmaps and engineering priorities. You will set measurement standards, guide distributed communication strategy and review critical C++ and Python tools.
The System Engineering Performance team 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 happens through evidence, technical ownership and direct cross-team influence.
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.
Benefits:
- Medical, dental, and vision coverage
- Mental health, wellness, and employee assistance resources
- Retirement savings benefits and company contributions
- Paid vacation, sick time, company holidays, and parental or family leave
- Life insurance and short-term or long-term disability coverage
- Flexible working hours and hybrid working arrangements