10 hours ago
Base Salary
$380k - $500k/yr
Responsibilities
- Optimize model execution on TPUs across model code, kernels, and hardware.
- Profile workloads, identify bottlenecks, and improve latency, throughput, and hardware utilization.
- Develop and optimize kernels based on model behavior and performance requirements.
- Explore quantization and related techniques to improve inference efficiency while preserving model quality.
- Build benchmarks and tools to measure performance, validate correctness, and guide optimization.
- Partner with researchers and engineers to support new model architectures and productionize performance improvements.
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 kernel behavior to complete-model performance across multiple layers of the stack.
- Strong software engineering skills and a systematic approach to profiling, debugging, and validating performance improvements.
- Ability to own open-ended technical problems, prioritize work, make design decisions, and deliver solutions.
- Collaborative communication skills and ability to explain technical tradeoffs.
- Experience with quantization or attention kernels is especially useful.
Categories
About OpenAI
OpenAI builds and deploys large-scale AI models and tools—including ChatGPT, GPT-4–class models, DALL·E, and Whisper—sold via APIs and enterprise subscriptions to developers and businesses. It monetizes through usage-based API pricing and ChatGPT Plus/Team/Enterprise, and also reaches customers via Microsoft’s Azure OpenAI Service. Founded in 2015 and headquartered in San Francisco, it operates as a private partnership.