Staff AI Performance Engineer
About the role
Graphcore’s AI/ML training and inference infrastructure is rapidly scaling to meet the growing demands of AI workloads across mobile, edge, and datacenter environments. This role focuses on optimizing performance across ARM-based architectures and large-scale distributed systems, ensuring efficiency, scalability, and reliability across the full hardware-software stack.
Responsibilities
- Analyze ML models’ compute and memory requirements using roofline analysis and simulations
- Collaborate across hardware and software teams to optimize large-scale AI workloads
- Benchmark, monitor, and troubleshoot system performance across distributed systems
- Optimize communication stacks including MPI, NCCL, UCX, RDMA, and networking fabrics
- Profile and optimize AI workloads, focusing on performance bottlenecks
- Develop high-quality, ARM-compatible code and documentation
Requirements
- BS/MS in Computer Science, Electrical Engineering, or related field
- Experience with distributed systems and communication libraries (MPI, NCCL, UCX, libfabric)
- Strong programming skills in C++ and Python
- Experience profiling and optimizing HPC or AI/ML workloads
- Familiarity with ML benchmarks such as MLPerf
Desired Skills
- Experience with GPUs or accelerated computing architectures
- Familiarity with HPC networking and interconnect technologies (InfiniBand, RoCE)
- Knowledge of ML frameworks such as PyTorch or TensorFlow
- Understanding of ARM architectures and toolchains
- Strong debugging, profiling, and performance optimization skills
Benefits
In addition to a competitive salary, Graphcore offers flexible working and a comprehensive benefits package designed to support your health, wellbeing and financial future. Our benefits include medical, dental and vision coverage, Flexible Spending Accounts (FSAs), Health Savings Accounts (HSAs), disability and life insurance, a 401(k) retirement plan, commuter benefits, wellness services and an Employee Assistance Programme (EAP).