Meta is seeking to solve cutting edge infrastructure problems at scale, specifically scalability bottlenecks in AI and Compute Fleet
Requirements
- Currently has, or is in the process of obtaining a PhD degree in Computer Science or a similar field
- Conducted research in ML systems, hardware/software co-design, inference/training efficiency, large scale infrastructure or related areas
- Track record of recent and consistent publications reflecting expertise in theoretical and/or empirical research
- Experience solving analytical problems using analytic and quantitative approaches
- Relevant research experience working on HW/SW for AI Infrastructure
- Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as publications at leading workshops, journals or conferences
- Experience with driving research in a large-scale distributed systems setup
Responsibilities
- Utilize extensive understanding of hardware architecture and software to analyze the scalability bottlenecks in our AI and Compute Fleet
- Conduct state-of-the-art research to advance the science and technology of AI infrastructure
- Collaborate closely with cross-functional partners across a broad range of disciplines and contribute towards Meta's research product development
- Influence progress of relevant research communities by producing high-quality publications
- Open source research code and conduct reproducible research
Other
- Currently has, or is in the process of obtaining a Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
- Must obtain work authorization in country of employment at the time of hire and maintain ongoing work authorization during employment
- Degree must be completed prior to joining Meta
- Experience solving complex problems and comparing alternative solutions, trade-offs, and varying perspectives to determine a path forward
- Must be willing to work in California, if hired for this position
