Research Scientist, Networking Research - PhD New College Grad 2026 - CA, Santa Clara, United States

Originally posted 18 September 2026 by the employer — open 1 day.

About the role

This role focuses on designing networks optimized for AI systems and leveraging AI and machine learning to advance network architecture and enable intelligent, real-time decision-making. You will invent new networking technologies to advance the performance, scalability, and efficiency of computing platforms.

What you'll do

• Develop network architectures, algorithms, and hardware/software co-design approaches for high-performance interconnects and distributed AI systems.
• Create and evaluate mechanisms for network and system decision-making in large-scale GPU/accelerator clusters, including AI/ML-based approaches for routing, traffic engineering, congestion control, scheduling, topology design, and telemetry-driven control loops.
• Invent new techniques, technologies, methodologies, processes, and devices, delivering prototypes, patents, publications, and product impact.
• Prototype new ideas in simulation or through analytical modeling.
• Participate in the broader research community by serving as a reviewer, on Program Committees, publishing papers, and speaking at conferences.
• Collaborate with external researchers, primarily in academia.

What you'll need

• Pursuing or recently completed a PhD in CS, CE, EE, Physics, Math, or equivalent experience.
• 2+ years of relevant industrial and academic experience, including systems and network design for AI or HPC infrastructure and/or applying AI/ML to systems or networking problems (e.g., optimization, reinforcement learning, graph learning, telemetry-driven control).
• Background and publication record in systems, networking, computer architecture, and/or ML for networking/systems.
• Evidence via publications plus artifacts (open-source, prototypes, production deployments) demonstrating impactful contributions to systems or network design for AI infrastructure, including where ML/RL informs design or drives online decisions.
• Strong programming and prototyping ability, with experience building research artifacts, simulators, or system prototypes; C++ and Python preferred.

Nice to have

• Publication at venues such as ISCA, HPCA, MICRO, SIGCOMM, NSDI.
• Experience with AI/ML methods for systems and networks supporting AI workloads (e.g., PyTorch/TensorFlow/JAX).
• Experience with hardware description languages or HLS.

Skills: network architectures, AI systems, machine learning, distributed AI systems, GPU/accelerator clusters