Research Scientist Intern, AI & System Co-Design (PhD)

Meta•Menlo Park, CA

1d•$7,650 - $12,667

About The Position

The AI System SW/HW Co-design team’s mission is to explore, develop, and help productize high-performance software and hardware technologies for AI at datacenter scale. We achieve this via concurrent design, performance projection, and optimization of many aspects of the system such as models, algorithms, numerics, performance, and AI hardware including compute, networking, and storage. We drive the AI HW roadmap at Meta and ensure our existing and future AI workloads and software are well optimized and suited for new infrastructure. The team works across HW types (GPUs, ASICs), workload types (Recommendation Models, LLM, LDM) and workloads (Training & Inference). Our team at Meta AI offers twelve (12) to twenty-four (24) weeks long internships and we have various start dates throughout the year.

Requirements

Currently has, or is in the process of obtaining a PhD degree in the field of Computer Science or a related STEM field
Strong knowledge of Hardware Architecture, Distributed systems, and AI Frameworks with interest in one or more of High Performance Computing, Numerics, Performance, and AI hardware including compute, networking, and storage
Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment

Nice To Haves

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, NSDI, MLSys, Neurips, ICML, ICLR, or similar
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
Experience in theoretical and empirical research and for answering questions with research
Experience communicating research for public audiences of peers
Experience working and communicating cross functionally in a team environment
Intent to return to the degree program after the completion of the internship/co-op

Responsibilities

Lead and support research that accelerates ML applications over one or more of software, system and accelerator architectures, optimizing training and/or inference of next generation AI workloads at Meta.
Work towards long-term ambitious research goals, while identifying intermediate milestones.
Lead and collaborate on research projects with other researchers and engineers across diverse disciplines.
Communicate research agenda, progress and results.
Influence progress of relevant research communities by producing publications.