Senior AI Networking Software Engineer (Remote)

Cornelis Networks; United States; On-site; USD 150,000 - 230,000; Full time

Benefits offered by this job

Equity

Health benefits

401(k) with company match

Open Time Off

Job summary

Cornelis Networks is seeking a highly experienced Senior Software Engineer to design, develop, and upstream-enable AI communication middleware for distributed AI workloads. You will optimize collective communication paths and performance across multi-node, multi-GPU configurations.

Work is remote within the United States. The role involves collaborating across kernel, driver, switch, and systems teams, with a focus on production-quality code and open-source contributions.

Qualifications

• 8+ years of experience in high-performance C/C++ on Linux.
• Strong experience with GPU communication stacks including CUDA/ROCm and NCCL/RCCL.
• Ability to optimize distributed training performance using profiling and tracing.
• Understanding of collective communication concepts and topology awareness.
• Experience delivering production-quality code and open-source contributions.

Responsibilities

• Design and implement performance-critical features for CCL enablement on Cornelis Networks’ fabrics.
• Optimize distributed training performance across multi-node, multi-GPU configurations.
• Profile distributed AI workloads to identify bottlenecks across software and hardware.
• Collaborate with kernel/driver, switch, performance, and systems teams.
• Contribute upstream to AI communication and distributed training projects.

Skills

C/C++ programming

Linux development

GPU communication stacks

Profiling & tracing

Distributed training optimization

Tools

CUDA

ROCm

NCCL/RCCL

Job description

Cornelis Networks is seeking a highly experienced Senior Software Engineer to design, develop, and upstream-enable AI communication middleware for distributed AI workloads. You will optimize collective communication paths and performance across multi-node, multi-GPU configurations.

Work is remote within the United States. The role involves collaborating across kernel, driver, switch, and systems teams, with a focus on production-quality code and open-source contributions.