Research Scientist, AI & Systems Co-design (PhD)

Job Title

Research Scientist, AI & Systems Co-design (PhD)

Role Summary

Work on co-design of models, runtimes, and hardware to improve scalability, efficiency, and reliability of datacenter-scale AI systems. The team spans exploration, prototyping, and productionization and collaborates with architecture, compiler, kernel, modeling, runtime, infrastructure, and product teams.

Experience Level

Mid-level research role. PhD preferred; candidates with a Master’s plus significant industry experience are considered (see Education Requirements).

Responsibilities

Deliver research and engineering that improves AI system performance and guides future hardware and software design.

• Co-design and optimize parallelism, compute efficiency, and distributed training/inference paradigms for generative AI systems.
• Develop model deployment techniques to improve sustained scaling and hardware efficiency during serving.
• Benchmark, profile, and model AI workloads to evaluate what-if scenarios and inform hardware, model, and runtime roadmaps.
• Prototype and help productionize optimized ML kernels to maximize accelerator performance.
• Lead cross-functional technical initiatives and provide feedback to architecture, compiler, kernel, and runtime teams.
• Guide system- and silicon-level HW requirements and technology evaluations for Meta’s future AI workloads.

Requirements

Must-have technical skills and experience.

• Proven research experience in hardware-aware model enablement, performance modeling of AI systems, or accelerator/silicon architectures.
• Hands-on experience with AI hardware architecture or on-device mapping/optimization for performance, power, and area (PPA).
• Theoretical and practical familiarity with modern AI models (e.g., CNNs, Transformers, LLMs, diffusion models).
• Experience in system-level performance analysis, profiling, and benchmarking of AI workloads.
• Strong Python skills and experience with at least one major AI framework (TensorFlow, PyTorch, JAX, etc.).
• Track record of publishing in peer-reviewed conferences or journals and communicating results to cross-functional stakeholders.

Nice-to-have (preferred):

• Experience deploying AI agents or efficiency techniques for production inference/serving.
• Experience with training/inference of large-scale deep learning models and distributed ML systems.
• Low-level programming experience for specialized hardware (CUDA, HIP, Triton) or hardware description languages (HDL).
• Familiarity with generative models (LLMs, latent diffusion) or recommendation models (e.g., DLRM).

Education Requirements

PhD in Computer Science, Electrical Engineering, Applied Mathematics, or a related technical field is preferred. Alternatively, a Master’s degree plus 3+ years of relevant industry experience is acceptable. Candidates must have completed a Bachelor’s degree in Computer Science, Computer Engineering, or a related technical field (or equivalent practical experience) prior to joining.

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.