Software Engineer, ML Networking

Anthropic; New York (NY); Hybrid; USD 280,000 - 850,000; Full time

Job summary

Anthropic is seeking a systems-level engineer specializing in network infrastructure to build and optimize software interfacing accelerators with high-speed networks.

You will work across kernel and user-space networking, dive into TCP/IP stack internals, XDP, eBPF, DPDK, and RDMA, and help design new network protocols for large-scale systems. A Bachelor’s degree is required and hybrid office presence is expected.

Qualifications

• Expertise in 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.
• Knowledge to build abstractions like collectives and RPC for distributed systems.
• Experience diagnosing networking issues in OSI layers 2-4.

Responsibilities

• Write and maintain software interfacing accelerators with high-speed networks.
• Diagnose and optimize distributed networking software across kernel and user space.
• Design and implement network protocols and performance optimizations.
• Collaborate with ML accelerator teams to improve data movement over networks.

Skills

Networking protocols

Kernel networking

User-space networking

OS/driver programming

Rust familiarity

Education

Bachelor's degree

Tools

DPDK

RDMA

io_uring

epoll

XDP

PCIe drivers

Job description

About Anthropic

Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.

Role Summary

A systems-level engineer specializing in network infrastructure and network optimization, with expertise in building and maintaining software that interacts with networks. You will be responsible for writing and maintaining software that interfaces between our accelerators and our high-speed networks. This role requires 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.

Networking Systems Engineering

You may be a good fit if you have:

• 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

Annual Salary

$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. However, some roles may require more time in our offices.

Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.

Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you’re ever unsure about a communication, don’t click any links—visit anthropic.com/careers directly for confirmed position openings.

How We're Different

We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We’re an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.

The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.

Come work with us!

Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.