- Develop tools and methodologies for large scale workload analysis and extract representative benchmarks (in C++/Python/Hack) to drive early evaluation of upcoming platforms.
- Analyze evolving Meta workload trends and business needs to derive requirements for future offerings. Apply in depth knowledge of how the AI/ML systems interact with the compute and storage systems around.
- Utilize extensive understanding of CPUs (x86/ARM), GPU (Nvidia/AMD/Intel), Collectives and systems to identify bottlenecks and enhance product/service efficiency. Collaborate closely with software developers to re-architect services, improve codebase through algorithm redesign, reduce resource consumption, and identify hardware/software co-design opportunities.
- Identify industry trends, analyze emerging technologies and disruptive paradigms. Conduct prototyping exercises to quantify the value proposition for Meta and develop adoption plans. Influence vendor hardware roadmap and broader ecosystem to align with Meta's roadmap requirements.
- Work with Software Services, Product Engineering, and Infrastructure Engineering teams to find the optimal way to deliver the hardware roadmap into production and drive adoption.
- Currently has, or is in the process of obtaining, PhD degree in the field of Computer Science or a related STEM field.
- Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment.
- Experience with hardware architecture, compute technologies and/or storage systems
- Intent to return to degree-program after the completion of the internship/co-op.
- Track record of achieving results as demonstrated by grants, fellowships, patents, as well as first-authored publications at leading workshops or conferences such as MICRO, ISCA, HPCA, ASPLOS, ATC, SOSP, OSDI, MLSys or similar.
- Architectural understanding of CPU, GPU, Accelerators, Networking, systems.
- Some experience with large-scale infrastructure, distributed systems, full stack analysis of server applications.
- Experience or knowledge in developing and debugging in C/C++, Python and/or PyTorch.
- Experience driving original scholarship in collaboration with a team.
- Experience leading a team in solving analytical problems using quantitative approaches.
- Interpersonal experience: cross-group and cross-culture collaboration.
- Experience in theoretical and empirical research and for answering questions with research.
- Experience communicating research for public audiences of peers.
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