Software Engineer, Inference - Performance Optimization
About the Team Our team analyzes inference stack performance across the application, model, and fleet layers to identify bottlenecks and drive faster, cheaper inference. We combine systems profiling, benchmarking, and analysis to understand where time and cost are spent, then turn that understanding into performance op
What this role actually needs.
About the Team Our team analyzes inference stack performance across the application, model, and fleet layers to identify bottlenecks and drive faster, cheaper inference. We combine systems profiling, benchmarking, and analysis to understand where time and cost are spent, then turn that understanding into performance op Responsibilities: - Build and refine performance models that translate microbenchmark results into cost-to-serve estimates. - Analyze inference workloads end to end across applications, models, and fleet infrastructure. - Enhance tooling to identify bottlenecks across layers for latency and throughput. - Partner with other teams to turn performance insights into concrete improvements and project how future changes affect inference. - Enjoy reasoning from first principles about distributed systems, model inference, and hardware efficiency. - Are comfortable working across abstraction layers, from application behavior to kernels, accelerators, networking, and fleet scheduling. 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 Software Engineer, Inference - Performance Optimization role.
- Build and refine performance models that translate microbenchmark results into cost-to-serve estimates.
- Analyze inference workloads end to end across applications, models, and fleet infrastructure.
- Enhance tooling to identify bottlenecks across layers for latency and throughput.
- Partner with other teams to turn performance insights into concrete improvements and project how future changes affect inference.
- Enjoy reasoning from first principles about distributed systems, model inference, and hardware efficiency.
- Are comfortable working across abstraction layers, from application behavior to kernels, accelerators, networking, and fleet scheduling.
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Source: jobs.ashbyhq.com · Source ID: 85fceac9-fb8a-4d71-a524-a8e5f1e9b01b · Confidence: 97/100 · Last checked: May 7, 2026
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