TPU Inference & Kernel Optimization Engineer

Openai; United States; Remote; USD 180,000 - 260,000; Full time

Job summary

OpenAI is seeking an engineer to lead the optimization of frontier models on TPUs, owning performance from model code through kernels to hardware execution. You will profile, identify bottlenecks, and drive improvements across latency, throughput, and hardware utilization.

The role welcomes experience from either training or inference, with a strong foundation in optimizing real workloads on TPUs. You will collaborate with researchers and engineers to scale performance into production and shape

Qualifications

• Experience optimizing ML workloads on TPUs in training or inference.
• Ability to map model computation to accelerator hardware.
• Strong software engineering and profiling skills.
• Ability to own complex technical problems end-to-end.

Responsibilities

• Profile workloads, identify bottlenecks, and implement improvements to latency, throughput, and hardware utilization.
• Develop and optimize kernels, using an understanding of the surrounding model to guide implementation choices.
• Explore techniques such as quantization to improve inference efficiency while preserving model quality.
• Build benchmarks and tools to measure performance, validate correctness, and guide optimization work.
• Partner with researchers and engineers to support new model architectures and bring performance improvements into production.

Skills

TPU optimization

Kernel optimization

Model architectures

Profiling & debugging

Quantization

Collaboration

Job description

OpenAI is seeking an engineer to lead the optimization of frontier models on TPUs, owning performance from model code through kernels to hardware execution. You will profile, identify bottlenecks, and drive improvements across latency, throughput, and hardware utilization.

The role welcomes experience from either training or inference, with a strong foundation in optimizing real workloads on TPUs. You will collaborate with researchers and engineers to scale performance into production and shape