AI Infrastructure Research Scientist - Scale & Innovate

ByteDance; San Jose (CA); On-site; USD 218,000 - 388,000; Full time

Job summary

ByteDance is seeking talented graduates to join our AI Factory Architecture team in 2027. You will design scalable AI infrastructure across the full stack for training, RL, and inference, working alongside engineers, researchers, and hardware specialists.

You will track trends in AI systems and cognitive science to inform memory and reasoning substrates, build prototypes, and help optimize performance of AI memory systems across the ML stack.

Qualifications

• PhD in CS/EE or related technical discipline; backgrounds in cognitive science or psychology welcome with strong systems fundamentals.
• Experience in distributed systems, infrastructure engineering, or ML systems and evaluating trade-offs across hardware, software, energy, and supply-chain constraints.
• Strong proficiency in integrating AI tools into knowledge discovery and research workflows.
• Demonstrated ability to learn quickly and stay productive in a fast-evolving technical horizon.
• Excellent communication skills to collaborate across teams.

Responsibilities

• Design and evaluate scalable architectures across the full AI factory for training, RL, and inference workloads.
• Track emerging trends in AI systems, distributed training, RL, and AI memory research; build prototypes and share insights.
• Analyze and optimize performance across the ML stack, including scheduling, networking, storage, and AI memory systems.
• Work cross-functionally with research, engineering, hardware, data-center, and product teams to translate AI workload requirements into scalable solutions.

Skills

Distributed systems

ML systems

Large-scale training

Research collaboration

Education

PhD in Computer Science/Engineering or related

Tools

NCCL

RDMA

Job description

ByteDance is seeking talented graduates to join our AI Factory Architecture team in 2027. You will design scalable AI infrastructure across the full stack for training, RL, and inference, working alongside engineers, researchers, and hardware specialists.

You will track trends in AI systems and cognitive science to inform memory and reasoning substrates, build prototypes, and help optimize performance of AI memory systems across the ML stack.