Meta - Menlo Park, CA

posted 2 months ago

Full-time
Menlo Park, CA
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About the position

Meta's AI Training and Inference Infrastructure is experiencing exponential growth to support an increasing array of AI use cases. This growth presents a significant scaling challenge that our engineers must address daily. The primary focus of this role is to build and evolve our network infrastructure, which connects numerous training accelerators, such as GPUs. It is crucial to ensure that the network operates smoothly and meets the stringent performance and availability requirements of RDMA workloads, which demand a loss-less fabric interconnect. To enhance the performance of these systems, we continuously seek opportunities across the entire stack, including network fabric, host networking, communication libraries, and scheduling infrastructure. As an AI/HPC Network Engineer, you will be responsible for designing, developing, testing, and operating networking systems that support large-scale AI training jobs. This involves researching, developing, and deploying various technologies and network topologies to evolve and scale our AI networks effectively. Collaboration is key in this role, as you will work closely with hardware, software, and sourcing teams to develop innovative networking solutions and influence the future of networking and its associated infrastructure. Additionally, you will define and develop optimized network monitoring systems to ensure the reliability and efficiency of our networks. Being on-call will also be part of your responsibilities, allowing you to learn from real-world production challenges and apply those lessons to improve current and future generation products.

Responsibilities

  • Design, develop, test and operate networking systems to support large scale AI training jobs.
  • Research, develop and deploy numerous technologies and network topologies in order to evolve and scale our AI networks.
  • Work closely with our hardware, software and sourcing teams to develop new networking solutions and influence the future of networking and its associated infrastructure.
  • Define and develop optimized network monitoring systems.
  • Be oncall to learn from real world production challenges and take the lessons to improve current and future generation products.

Requirements

  • Engineering degree, or a related technical discipline or equivalent experience.
  • Experience coding in languages like Python, C++, Go, etc.
  • Experience in network automation software leveraging software defined networking principles.
  • Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.
  • Experience in designing, deploying and operating networks at scale.

Nice-to-haves

  • BS or MS in Computer Science or Computer Engineering
  • Expert Knowledge of IB/RDMA/RoCE Networks
  • 4+ years of experience working on networks supporting large scale training workloads
  • Understanding of routing and switching - hardware design and knowledge of forwarding and data planes
  • Understanding of AI training workloads and demands they exert on networks.
  • Understanding of RDMA congestion control mechanisms on IB and RoCE Networks.
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