Software Engineer, ML Networking

Software Engineer, ML Networking

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.

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.

• Expert‑level proficiency with network protocols and networking concepts
• Deep kernel networking: TCP/IP stack internals, XDP, eBPF, , 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

• 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 expected base compensation for this position is below. Our total compensation package for full‑time employees includes equity, benefits, and may include incentive compensation.

Annual Salary
$315,000—$560,000 USD

Education requirements:

We require at least a Bachelor’s degree in a related field or equivalent experience.
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.

We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work.

We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.

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…