Workload Porting & Performance Engineer
About the Team OpenAI’s Infrastructure organization builds and evaluates the systems that power advanced AI workloads. We work closely with hardware, modeling, and architecture teams to ensure that new platforms deliver real-world performance aligned with workload needs.
What this role actually needs.
About the Team OpenAI’s Infrastructure organization builds and evaluates the systems that power advanced AI workloads. We work closely with hardware, modeling, and architecture teams to ensure that new platforms deliver real-world performance aligned with workload needs. 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 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. Company context: OpenAI builds frontier AI systems, research infrastructure, and applied products for developers, enterprises, and global users.
Day-to-day expectations
OpenAI lists these responsibilities for the Workload Porting & Performance Engineer role.
- 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
What a strong candidate brings
These requirements are extracted from the source listing and normalized for UpJobz readers.
- 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.
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Source: jobs.ashbyhq.com · Source ID: ec0a4e03-bbcc-4c64-813f-b53dabb8f53a · Confidence: 97/100 · Last checked: May 7, 2026
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