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.
XPENG provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.
