Meta is seeking to drive the definition of next-generation compute and storage architectures for AI systems, ensuring that existing and future AI workloads and software are well optimized and suited for the hardware infrastructure.
Requirements
- Experience with hardware architecture, compute technologies and/or storage systems
- Architectural understanding of CPU, GPU, Accelerators, Networking, Flash/HDD Storage 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
- Demonstrated software engineer experience via an internship, work experience, coding competitions, or widely used contributions in open source repositories (e.g. GitHub)
Responsibilities
- 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.
- Utilize extensive understanding of CPUs (x86/ARM), Flash/HDD storage systems, networking, and GPUs to identify bottlenecks and enhance product/service efficiency.
- 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.
Other
- 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
- 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
- Experience communicating research for public audiences of peers
