Software Engineer, ML Networking

Highlights

• Build systems for accelerator-initiated tensor movement over high-speed networks.
• Optimize congestion control algorithms for large-scale synchronous workloads.
• Implement new collective algorithms to improve latency across distributed systems.

What they offer

• Competitive compensation and benefits
• Optional equity donation matching
• Generous vacation and parental leave
• Flexible working hours

Ideal candidate

A systems-level problem solver who thrives debugging complex distributed issues and building high-performance network infrastructure for AI workloads.

Requirements

• Expert-level proficiency with network protocols and networking concepts
• Deep kernel networking experience including TCP/IP internals, XDP, eBPF, io_uring and epoll
• User-space networking experience including DPDK, RDMA and kernel bypass techniques
• Ability to build higher-level abstractions like collectives and RPC
• Skilled at diagnosing distributed networking issues, especially OSI layers 2-4
• Strong systems programming skills including memory management and NUMA-aware programming
• Bachelor's degree or equivalent combination of education, training and experience