Senior AI Performance Engineer

US - Austinfull timeOn Site

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senior

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Graphcore Senior AI Performance Engineer at Graphcore responsible for analyzing and optimizing AI training and inference workloads across large-scale distributed systems. Designs benchmarks and optimizes distributed communication software using technologies such as MPI, NCCL, UCX, and RDMA.

Responsibilities

This role gives you rare scope across hardware, software, networking and system architecture. It is based in Austin, Texas.
The team and culture
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 moves through evidence, ownership and clear technical judgment. You will define investigations, coordinate across teams and validate impact with reliable performance data.
Decisions are shaped through benchmarks, models, simulations and practical engineering tradeoffs. The team values engineers who think big, act fast, take responsibility, speak up and lead beyond their own area.

Qualification

Strong C++ and Python skillsDeep understanding of computeFamiliarity with MLPerfFamiliarity with ML frameworks

Required

Strong experience profiling and optimizing AI, machine learning or high-performance computing workloads.
Experience with distributed systems and communication libraries such as MPI, NCCL, UCX or libfabric.
Strong C++ and Python skills, including reliable tools or performance-sensitive software.
Deep understanding of compute, memory and communication behavior in large-scale systems.
Ability to own complex technical work and coordinate improvements across teams.
Familiarity with MLPerf, accelerated architectures, ML frameworks or high-performance interconnects.
While we have outlined a set of requirements, we value transferable skills and diverse experiences. We also welcome engineers returning to the profession after a career break, including through returnship routes.

Preferred

Familiarity with MLPerf
Familiarity with accelerated architectures
Familiarity with ML frameworks
Familiarity with high-performance interconnects

Benefits

Dental
Vision
Parental Leave
Life Insurance
Wellness

Company

Graphcore

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Source: greenhouse

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