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1 день назад

Network Systems Architect (AI)

Формат работы
hybrid
Тип работы
fulltime
Грейд
senior
Английский
b2
Страна
US
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

Текст:
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TL;DR
Network Systems Architect (AI): Defining multi-generation scale-up network architectures, proprietary accelerator interconnects, protocols, and switching for Cerebras AI platforms with an accent on low-latency fabrics, workload communication patterns, and cross-layer system requirements. Focus on designing topology, routing, buffering, flow control, reliability, and fault containment, then validating decisions through performance models, simulations, prototypes, implementation, and qualification.

Location: Sunnyvale, CA; hybrid

Company

hirify.global builds large-scale AI accelerator hardware and platforms designed to deliver high-speed model training and inference.

What you will do

  • Define multi-generation scale-up network architectures and roadmaps, including interfaces to scale-out and customer-facing networks.
  • Work with application, compiler, runtime, and communication-library teams to translate workload behavior into bandwidth, latency, ordering, availability, and serviceability requirements.
  • Design fabric topology, protocols, routing, buffering, flow control, reliability, and fault-containment behavior.
  • Evaluate standards-based technologies, merchant silicon, and custom protocols, switches, links, or offloads.
  • Use performance models, traffic simulations, prototypes, and lab data to validate architecture choices and define acceptance criteria.
  • Write architecture and interface specifications, lead design reviews, and guide implementation, bring-up, and qualification.

Requirements

  • Hands-on experience with low-level network or systems implementation, modeling, bring-up, or debugging.
  • Experience designing low-latency scale-up or system fabrics and understanding scale-out network boundaries.
  • Knowledge of network topology, protocols, switching, routing, buffering, flow control, reliability, and fault containment.
  • Ability to analyze workload partitioning, placement, data and memory movement, synchronization, locality, and failure behavior.
  • Ability to make cross-layer architectural decisions and drive designs through implementation and qualification.

Culture & Benefits

  • Opportunity to build AI platforms beyond conventional GPU constraints.
  • Access to cutting-edge AI research, including publishing and open-source opportunities.
  • Work on high-performance AI supercomputing systems.
  • Startup vitality combined with job stability.
  • Non-corporate culture focused on individual respect, inclusion, learning, and professional growth.

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