The opportunity
Our Inference team brings OpenAI’s most capable research and technology to the world through our products. We empower consumers, enterprises and developers alike to use and access our state-of-the-art AI models, allowing them to do things that they’ve never been able to before.
What you'll do
Optimize model execution on TPUs, improving performance across the complete: forward pass and the interactions between model code, kernels, and hardware.
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.
What they're looking for
- Have practical experience optimizing machine learning workloads on TPUs, through training, inference, or both.
- Understand modern model architectures and how their computation maps onto accelerator hardware.
- Can connect detailed kernel behavior to the performance of a complete model: and work across these layers of the stack.
- Bring strong software engineering skills and a systematic approach to: profiling, debugging, and validating performance improvements.
