AI Performance Engineer

Graphcore

$120K — $160K *
Technical Services
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 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

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

Benefits

  • Opportunity to work at the forefront of AI and hardware innovation
  • Collaborative and diverse team environment
  • Continuous learning culture
  • Engagement with cutting-edge technology and transformative projects
  • Part of a larger organization with robust resources and capabilities
Full Job Description
Job Summary

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.
The Team

The System Engineering Performance team architects and optimizes high-performance infrastructure for large-scale datacenter deployments. The team works across hardware, software, networking, and system architecture to deliver cutting-edge AI solutions and ensure optimal system performance at scale.
Responsibilities and Duties
  • 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
Candidate Profile

Essential:
  • 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

Desirable:
  • Experience with GPUs or accelerated computing architectures
  • Knowledge of HPC networking and interconnect technologies (InfiniBand, RoCE)
  • Familiarity with ML frameworks such as PyTorch or TensorFlow
  • Understanding of ARM architectures and toolchains
  • Strong debugging, profiling, and performance optimization skills

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).

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