Software Engineer, ML Networking at Anthropic

Hybrid - San Francisco, CA | New York City, NY | Seattle, WA

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Software Engineer, ML Networking at Anthropic is responsible for building and maintaining systems-level software that connects machine learning accelerators to high-speed networks. The role requires deep knowledge of networking protocols, kernel-space and user-space networking, and low-level systems programming. Candidates will write and optimize distributed network software, design new protocols, and benchmark performance across a variety of networking environments. The position is part of the AI Research & Engineering department and supports Anthropic’s mission to create safe and beneficial AI systems.

Salary

USD 280,000 - 850,000

Requirements

Skills

  • Expert-level proficiency with network protocols and networking concepts
  • Deep kernel networking: TCP/IP stack internals, XDP, eBPF, io_uring, and epoll
  • User-space networking: DPDK, RDMA, kernel bypass techniques
  • Understanding of how to build higher-level abstractions like collectives and RPC
  • Skilled at diagnosing and resolving networking issues in distributed systems, especially at OSI model layers 2-4
  • Strong programming skills in a systems programming language, including memory management, lock-free data structures, and NUMA-aware programming
  • Software, driver, and OS performance optimization tools and techniques
  • Comfort with or desire to learn Rust
  • Understanding of ML accelerators and accelerator drivers
  • Demonstrated ability to design new network protocols
  • Experience with PCIe and drivers for PCIe devices
  • Expertise in algorithms used in networking, including compression and graph algorithms
  • Experience programming on SmartNICs
  • 5+ years of experience in systems programming or network programming
  • Often comes from backgrounds in: HPC, telecommunications, host networking software, OS/kernel engineering, or embedded systems
  • Strong debugging mindset with patience for complex, multi-layered issues

Responsibilities

  • Write and maintain software that interfaces between accelerators and high-speed networks
  • Build and maintain systems-level software for network infrastructure and optimization
  • Debug and optimize distributed software at the network level
  • Design and implement new network protocols and collective algorithms
  • Benchmark software for new networking environments
  • Optimize congestion control algorithms for large-scale synchronous workloads
  • Debug kernel-level network latency spikes

Technologies

TCP/IP stack internalsXDPeBPFio_uringepollDPDKRDMAKernel bypass techniquesHigher-level abstractions such as collectives and RPCRustML acceleratorsPCIeSmartNICsCompression algorithmsGraph algorithms

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