AI-Infra Network Architect Job Description

We seek a highly motivated Senior AI Network System Architect to join our team of experts and help shape the future of high-performance and ML / AI computing.

What You’ll Be Doing:

• Investigating emerging technologies and methodologies in ML and AI to discern their interactions with network infrastructure.
• Executing workloads on AI systems, conducting profiling, and analysing bottlenecks and possible enhancements.
• Conducting research and implementing optimizations for communication libraries like NCCL and UCX.
• Spearheading the conceptualization of next-generation networking products tailored to support and accelerate state-of-the-art ML workloads.
• Experience on network engineering and fine tuning to support models simulations, analyse simulation results, and optimization algorithms.
• Collaborate with multi-functional teams, including other architecture teams, logic design, system software, firmware, and ML research teams, to ensure the successful execution of the project.

What We Need to See:

·        Extensive expertise in ML/AI workloads, particularly in distributed training.

·        Excellent understanding of large-scale network behaviour and the effect of distributed computing workloads on the network.

·        Experience in the development of simulation environments.

·        Great problem-solving and critical-thinking skills.

·        Ability to thrive in a fast-paced and dynamic environment is necessary.

·        Ability to work concurrently with multiple groups in the organization.

Ways to Stand Out from The Crowd:

·        Knowledge of communication libraries such as NCCL, UCX, and UCC.

·        Good knowledge of network protocols - such as InfiniBand, IP, TCP, RoCE, and network topologies.

·        Awareness of Python, C++, and dockers.

·        Expertise in system engineering, operations research, and intricate hardware-software integrated systems.

·        Demonstrated experience in DLRM, LLM or other generative AI.

·        M.Sc, or Ph. D degree in Computer Science, Computer Engineering, or Electrical Engineering.

·        At least 2+ years of industry or research experience in computer networks.