Principal AI Performance Engineer

Graphcore • Austin, TX

21h • Hybrid

About The Position

Set the performance direction behind large-scale AI systems built for real deployment. 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. Your judgment will help teams make better decisions when data is incomplete. This role gives you rare influence across AI infrastructure at data center scale. It is based in Austin, Texas. 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. You will guide strategy, resolve complex tradeoffs and raise performance-engineering standards across the organization. Decisions are shaped by benchmarks, simulations, models and clear technical debate. The team values engineers who think big, act fast, take responsibility, speak up and lead beyond their own area.

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.

Nice To Haves

• Experience with MPI, NCCL, UCX, libfabric, MLPerf, accelerated architectures or high-performance interconnects.
• Transferable skills and diverse experiences.
• Engineers returning to the profession after a career break, including through returnship routes.

Responsibilities

• Define how Graphcore analyzes and optimizes AI training and inference workloads.
• Shape decisions across hardware, software, networking and system architecture.
• Lead performance investigations, from model behavior to multi-node scaling.
• Turn profiling, benchmarking and modeling evidence into technical roadmaps and engineering priorities.
• Set measurement standards, guide distributed communication strategy and review critical C++ and Python tools.
• Architect, evaluate and optimize high-performance infrastructure for large-scale data center deployments.
• Guide strategy, resolve complex tradeoffs and raise performance-engineering standards across the organization.

Benefits

• Medical, dental, and vision coverage, with options that may extend to eligible dependents.
• Mental health, wellness, and employee assistance resources.
• Retirement savings benefits and company contributions where applicable.
• Paid vacation, sick time, company holidays, and parental or family leave in accordance with applicable plans and policies.
• Life insurance and short-term or long-term disability coverage.
• Flexible working hours and hybrid working arrangements where compatible with the role and team requirements.
• Professional-development resources, learning programs, office amenities, and team-led activities.

What This Job Offers

• Job Type: Full-time
• Career Level: Principal
• Education Level: No Education Listed