Workload Porting & Performance Engineer

OpenAI•San Francisco, CA

1d•Hybrid

About The Position

OpenAI’s Infrastructure organization builds and evaluates the systems that power advanced AI workloads, focusing on understanding workload behavior across evolving hardware platforms and bridging the gap between theoretical capability and observed system performance. The Workload Porting & Performance Engineer will evaluate new hardware platforms by porting benchmarks and real-world workloads, analyzing performance, and identifying system bottlenecks. This role involves bringing up workloads on new systems, characterizing performance behavior, and adapting workloads to better utilize hardware capabilities. It is critical for validating new platforms and ensuring performance aligns with expectations across compute, memory, and networking subsystems. The position requires strong hands-on experience with performance analysis, workload optimization, and system-level debugging across hardware and software boundaries. This role is based in San Francisco, CA, and operates under a hybrid work model requiring 3 days in the office per week, with relocation assistance offered.

Requirements

Experience with performance analysis, benchmarking, or workload optimization.
Strong understanding of system architecture, including CPU/GPU, memory, and I/O subsystems.
Experience porting or adapting workloads across different hardware platforms.
Familiarity with profiling tools and performance debugging techniques.
Ability to identify root causes of performance issues across hardware/software boundaries.
Experience working in large-scale or distributed system environments.

Nice To Haves

Experience with AI/ML workloads, including training or inference systems.
Familiarity with GPU or accelerator-based systems.
Experience working with low-level performance tools (profilers, tracing, microbenchmarks).
Background in systems software, compilers, or runtime optimization.
Experience collaborating with hardware and architecture teams on performance validation.

Responsibilities

Port and enable benchmarks and real-world workloads on new hardware platforms.
Evaluate system performance across compute, memory, storage, and networking subsystems.
Identify and analyze performance bottlenecks and inefficiencies.
Adapt and optimize workloads to better utilize hardware capabilities.
Develop and run performance experiments and profiling workflows.
Compare expected vs. observed performance and provide feedback to: hardware architecture teams, performance modeling teams, system and software engineers.
Debug issues across the stack, including software, runtime, and hardware interactions.
Provide actionable insights to guide platform readiness and deployment decisions.