Job Summary
This position is responsible for overseeing the performance, scaling efficiency, and reliability of foundation-model training across a vast network of accelerators. The selected candidate will deliver technical leadership across various teams, focusing on identifying and resolving bottlenecks and developing intelligent automation to enhance engineering workflows.
Responsibilities
- Ensure optimal performance and scalability of foundation-model training.
- Lead cross-team initiatives to troubleshoot and optimize performance bottlenecks.
- Develop and implement automation solutions to improve engineering processes.
- Collaborate with multiple teams to align technical strategies and initiatives.
Qualifications
- A Master’s or PhD in Computer Science, Computer Engineering, or Electrical Engineering.
- Over 8 years of relevant industry experience, particularly in performance engineering.
- Expertise in programming languages such as C++ and Python.
- Strong understanding of GPU optimization practices, especially at a multi-node scale.
