The Research Scientist role in AI & Systems Co-Design at Meta focuses on exploring and optimizing high-performance software and hardware technologies for AI at datacenter scale. The team collaborates closely with product teams and invests in model optimization to improve performance and reduce costs for AI services. This position involves significant research and innovation in areas such as model deployment techniques and performance modeling of AI workloads. The role also includes guiding the hardware roadmap for Meta's custom AI accelerators and leading cross-functional initiatives.

• PhD in Computer Science, Electrical Engineering, Applied Mathematics, or a related technical field, OR a Master's degree with 3+ years of relevant industry experience.
• Proven research experience in hardware-aware model enablement, performance modeling of AI systems, or prevailing accelerators/silicon architectures.
• Hands-on proficiency with end-to-end AI hardware architecture or on-device mapping algorithm development.
• Theoretical background and practical experience with AI models such as CNNs, Transformers, LLMs, and Diffusion models.
• Experience in system-level performance analysis, profiling, and benchmarking of AI workloads.
• In-depth experience of Python and experience with at least one major AI framework.
• Track record of publishing research papers at peer-reviewed conferences or journals.

• Explore, co-design and optimize parallelisms, compute efficiency, distributed training/inference paradigms and algorithms to improve the scalability, efficiency, and reliability of GenAI systems.
• Innovate and co-design novel model deployment techniques for sustained scaling and hardware efficiency during GenAI serving.
• Benchmark, analyze, model, and project the performance of AI workloads against a wide range of what-if scenarios.
• Explore, prototype and productionize highly optimized ML kernels to unlock the full potential of current and future accelerators for Meta's AI workloads.
• Influence the hardware roadmap of Meta's custom AI accelerators.
• Lead cross-functional initiatives spanning multiple engineering organizations to drive high-impact technical milestones.
• Guide Meta's AI HW requirements and design focusing on performance at System and Silicon levels.

• Employees at Meta are often offered comprehensive benefits, including medical/dental/vision coverage, mental-health resources, family planning support (fertility, adoption, surrogacy), and caregiving programs. Financial benefits typically include a competitive retirement plan, equity awards, life insurance, and access to financial coaching and legal support. Time-off benefits commonly feature generous PTO and holidays, unlimited sick time, various paid leaves, flexible “Global Travel Days,” and a 30-day paid break every five years.