AI Systems Engineer – Serverless Distributed Computing

The Distributed Data Storage and Management Lab leads research in distributed data systems, aiming to develop next-generation cloud serverless products that encompass core infrastructure and databases. This lab addresses various data challenges, including cloud-native disaggregated databases, pay-by-query user models, and optimizing low-level data transfers via RDMA. Teams within this lab create advanced cloud serverless data infrastructure and implement cutting-edge networking technologies for Huawei's global AI infrastructure.

• Architect and develop frameworks and engines for next-generation serverless computing tailored to AI workloads (LLM training/inference, agent execution, RL training, etc.).

• Analyze and optimize end-to-end AI system performance, including distributed scheduling, data flow, and memory utilization across large clusters.

• Research and evaluate cutting-edge technologies in distributed computing, serverless infrastructure, reinforcement learning, and LLM-based AI agents.

• Collaborate cross-functionally with research, product, and platform teams to transform conceptual AI agent or RL research into scalable production systems.

• Contribute thought leadership through innovation, technical presentations, and patent generation.

• Stay ahead of industry trends, assessing emerging tools and frameworks (e.g., Ray, SkyPilot, vLLM, DeepSpeed, Mojo, etc.) to inform team.

The total target annual compensation for this position ranges from $127,000 to $225,000 depending on education, experience, and demonstrated expertise.