Tech Stack
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
AI
Debugging @ 6
Machine Learning @ 3
Profiling @ 6
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
The Inference team brings OpenAI’s research and technology to consumers, enterprises, and developers through its products. The team focuses on performant and efficient model inference and accelerating research through model inference.
Responsibilities
- Optimize model execution on TPUs across the complete forward pass and the interactions between model code, kernels, and hardware.
- Profile workloads, identify bottlenecks, and improve 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.
Requirements
- Practical experience optimizing machine learning workloads on TPUs through training, inference, or both.
- Understanding of modern model architectures and how their computation maps onto accelerator hardware.
- Ability to connect detailed kernel behavior to complete-model performance and work across these layers of the stack.
- Strong software engineering skills and a systematic approach to profiling, debugging, and validating performance improvements.
- Ability to take ownership of open-ended technical problems, identify priorities, make design decisions, and deliver working solutions.
- Collaborative approach to working with researchers and engineers, learning unfamiliar systems, and communicating technical tradeoffs.
- Experience with quantization or attention kernels is especially useful.
About OpenAI
OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. The company is an equal opportunity employer and provides reasonable accommodations to applicants with disabilities.
Compensation and Benefits
The base salary range is $380,000–$500,000, and the role offers equity. Total compensation may also include performance-related bonuses and benefits such as medical, dental, and vision insurance; health savings account contributions; pre-tax accounts; a 401(k) plan with employer match; paid parental, medical, and caregiver leave; paid time off; paid holidays; mental health and wellness support; employer-paid life and disability coverage; a learning and development stipend; office meals and meal delivery credits; relocation support for eligible employees; and other taxable fringe benefits.