We are hiring PhD students for research-focused internships in Summer 2027.
We are using this
Google form to get an early start on hiring. A more formal job posting will come later in Fall 2026.
We're excited to welcome
Cong Guo and
Youhe Jiang as postdocs starting Fall 2026.
- Cong joins us from Duke - he works on computer architecture, hardware-software co-design, and efficient AI systems, with an emphasis on model compression, quantization, and architectural designs for LLM.
- Youhe joins us from Cambridge - he focuses on building efficient large-scale distributed systems for AI, including LLM serving, distributed training, and heterogeneous resource optimization.
Jovan Stojkovic, our postdoc from 2025-2026, has joined Texas as an assistant professor - he will continue to work with us part-time on cloud-native workloads, datacenters, and systems-level optimization for ML.
About Us
The AI and Systems Co-Design team at Meta (formerly known as Facebook), led by CQ Tang (a.k.a. Chunqiang Tang), consists of over 100 employees, mostly PhDs, including many world-class research scientists and engineers.
As reflected in our team name "co-design", we conduct interdisciplinary research and development across AI, hardware, and software, with a focus on performance, efficiency, and scalability.
- We own the company's overall strategy for exploring innovative hardware technologies for CPUs, GPUs, memory, storage, and Meta's custom AI chips, and we productionize them in Meta's hyperscale fleet of O(1,000,000) servers and O(100,000) GPUs, powering all Meta products such as Facebook, Instagram, and Meta AI.
- We apply novel optimizations across the whole stack—hardware, ML models, ML systems, applications, and the Linux kernel—to achieve optimal performance.
- We develop innovative AI technologies for large language models (Llama), recommender systems, and more.
In addition to the real-world impact on billions of users of the Meta products, our team members have won Best Paper Awards at prestigious conferences such as ISCA, ASPLOS, SOSP, and OSDI, with multiple papers selected for IEEE Micro Top Picks. Additionally, we regularly publish in other areas such as ICML, NeurIPS, SC, HPCA, NSDI, VLDB, and MLSys. Overall, our work largely corresponds to the research communities of systems in general and especially systems for ML (MLSys, SOSP, OSDI, SIGCOMM, NSDI), hardware architecture (ISCA, ASPLOS), ML (NeurIPS, ICML, ICLR) and supercomputing (SC, ICS).
How We Work
Like research labs, our team consists primarily of PhDs. However, we differ from traditional research labs in several key ways:
- Direct ownership: Like traditional research labs, we build strong partnerships with numerous teams across diverse areas for broad influence. However, what sets us apart is our direct ownership of the hardware strategy for Meta's hyperscale fleet. This enables us to lead in many areas while fostering seamless partnerships in others.
- Production systems: Our primary goal is to develop forward-looking innovations in AI, hardware, and software, and directly implement them in production systems that serve billions of people. The billions of users of Meta products and Meta's hyperscale fleet of O(1,000,000) servers and O(100,000) GPUs are, in effect, our lab. In contrast, traditional research labs often rely on technology transfer for a less direct impact.
- Impact: Our impact is widely acknowledged within the company and throughout the industry. We drive Meta's hardware strategy to save billions of dollars, and directly develop innovative technologies in Meta's flagship products like Llama and Ads ranking models.
