Research Scientist, AI & Systems Co-Design (PhD)
Meta PlatformsJob Title
Research Scientist, AI & Systems Co-Design (PhD)
Role Summary
Research and develop high-performance software and hardware technologies for AI at datacenter scale. Work spans model, runtime, kernels, compilers, and hardware co-design to improve performance, efficiency, and scalability of generative AI and recommendation systems.
Collaborate with engineering, product, and infrastructure teams to prototype, benchmark, and productionize model-system co-design ideas and provide guidance on future hardware and system requirements.
Experience Level
Mid-level. PhD required (completed or near completion). No explicit years-of-experience stated.
Responsibilities
Key responsibilities include research, prototyping, and cross-functional delivery.
- Co-design and optimize parallelism, compute efficiency, distributed training/inference paradigms, and algorithms for GenAI and recommendation workloads.
- Innovate model deployment techniques to improve sustained scaling and hardware efficiency for model serving.
- Prototype and productionize optimized ML kernels to maximize utilization of current and future accelerators.
- Benchmark, profile, analyze, and model AI workload performance across what-if scenarios to inform hardware, model, and runtime design.
- Provide system- and silicon-level guidance for AI hardware requirements and collaborate with architecture, compiler, kernel, and runtime teams.
- Lead cross-functional initiatives to deliver high-impact technical milestones from research to production.
Requirements
Must-have research and technical skills; preferred items listed separately.
Must-have:- Proven research experience in computer architecture, operating systems, ML systems and kernels, ML compilers, model-system co-design, or performance modeling of AI systems.
- Hands-on experience with end-to-end AI hardware architecture or on-device mapping algorithm development, including performance/power/area (PPA) tradeoffs.
- Theoretical background and practical experience with AI models (e.g., Transformers, LLMs, Diffusion models, CNNs, recommendation models).
- Experience in system-level performance analysis, profiling, and benchmarking of AI workloads.
- Proficiency in Python and experience building production-quality code or research prototypes; experience with at least one major AI framework.
- Track record of publishing in peer-reviewed conferences or journals and communicating technical results to cross-functional stakeholders.
- Experience or knowledge of distributed machine learning systems and related algorithm development.
- Familiarity with training/inference of large-scale deep learning models and GenAI models (LLMs, LDMs) or ranking/recommendation models (e.g., DLRM).
- Experience with low-level programming for specialized hardware (CUDA, HIP, Triton) or hardware description languages (HDL).
- Experience deploying AI agents or optimizations for inference efficiency; patents, grants, fellowships, or first-authored publications are a plus.
- Experience working and communicating cross-functionally in large organizations.
Education Requirements
PhD in Computer Science, Electrical Engineering, Applied Mathematics, or a related technical field (completed or near completion). The posting also references a Bachelor's degree in Computer Science, Computer Engineering, or a relevant technical field (must be completed prior to start) and allows for equivalent practical experience.
Learn more about the team: https://aisystemcodesign.github.io
About the Company
Company: Meta Platforms
Headquarters: Menlo Park, California, United States
American technology company that develops social networking products (Facebook, Instagram, WhatsApp) and invests in virtual/augmented reality hardware and software through Reality Labs, focusing on connectivity, advertising, and immersive computing experiences.
