Staff AI Performance Engineer

EngineersOfAI; Austin (TX); On-site; USD 90,000 - 120,000; Full time

Job summary

EngineersOfAI is seeking a candidate to optimize AI workloads across various architectures. The role involves collaboration with hardware and software teams to ensure efficient performance of AI/ML models, as well as benchmarking and troubleshooting at scale.

The ideal applicant has a BS/MS in Computer Science or a related field, with strong programming skills in C++ and Python, and experience with distributed systems. This position offers opportunities to work on cutting-edge technology in Austin, Texas.

Qualifications

• Strong programming skills in C++ and Python.
• Experience with distributed systems and communication libraries.
• Experience profiling and optimizing HPC or AI/ML workloads.

Responsibilities

• Analyze ML models’ compute and memory requirements.
• Collaborate across hardware and software teams.
• Benchmark and troubleshoot system performance.

Skills

C++

Python

Distributed systems

Communication libraries (MPI, NCCL, UCX)

Profiling and optimizing HPC or AI/ML workloads

Education

BS/MS in Computer Science, Electrical Engineering, or related field

Tools

ML frameworks (PyTorch, TensorFlow)

HPC networking technologies (InfiniBand, RoCE)

Job description

About us

Graphcore is one of the world’s leading innovators in Artificial Intelligence compute.

It is developing hardware, software and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry.

As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone.

Graphcore’s teams are drawn from diverse backgrounds and bring a broad range of skills and perspectives. A melting pot of AI research specialists, silicon designers, software engineers and systems architects, Graphcore enjoys a culture of continuous learning and constant innovation.

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