Software Engineer, ML Networking

Anthropic's mission is to create reliable, interpretable, and steerable AI systems.

You will be a systems-level engineer specializing in network infrastructure and network optimization, with expertise in building and maintaining software that interacts with networks.

Responsibilities:

• Write and maintain software that interfaces between accelerators and high-speed networks.
• Require deep technical knowledge of network protocols, kernel-space and/or user-space networks, interfacing with hardware, and the ability to debug and optimize distributed software at the network level.

Requirements:

Networking Systems Engineering:

• 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

Low-Level Systems and OS Programming:

• 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

Strong candidates may have:

• 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

Representative Projects:

• Build a system for accelerator-initiated tensor movement over the network
• Benchmark software for a new networking environment
• Implement a new collective algorithm to improve latency
• Optimize congestion control algorithms for large-scale synchronous workloads
• Debug kernel-level network latency spikes

The annual compensation range for this role is $280,000-$850,000 USD.

Logistics

• Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience
• Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience
• Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position
• Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time.
• Visa sponsorship: We do sponsor visas!