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# Software Engineer - AI Middleware

- **Company:** Cornelis Networks
- **Location:** Austin, TX, United States (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Adobe InDesign, Artificial Intelligence, C++ (Programming Language), Code Review, Nvidia CUDA, Linux, Distributed Computing Environment, Ethernet, Remote Direct Memory Access, Tensorflow, System Programming, Performance Testing, Pytorch, Free and Open-Source Software, Cerner CCL
- **Published:** June 24, 2026
- **Apply:** https://www.dice.com/job-detail/0fc3e4df-2950-4ad8-95cd-ff8408a9eb54

## About the Role

* 8+ years of experience in high-performance systems programming in 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.
 * Open-source contributions in relevant areas.

Preferred Qualifications

 * Experience with AI frameworks such as PyTorch Distributed, DeepSpeed, and Megatron-LM.
 * Familiarity with libfabric/OFI, UCX, and RDMA concepts.
 * Experience with RoCEv2 and Ultra Ethernet.
 * Experience building cluster-scale performance test infrastructure.

## Description

* Design and implement performance-critical features for CCL enablement on Cornelis Networks' fabrics.
 * Optimize distributed training performance across multi-node, multi-GPU configurations.
 * Improve GPU communication paths including GPU-direct transfers, IPC, and CPU/GPU synchronization.
 * Profile distributed AI workloads and identify bottlenecks across the software and hardware stack.
 * Tune AI frameworks such as PyTorch Distributed, TensorFlow/XLA, JAX, DeepSpeed, and Megatron-LM.
 * Develop benchmarks and microbenchmarks aligned with real model performance.
 * Contribute upstream to AI communication and distributed training projects.
 * Participate in design reviews, code reviews, CI, and long-term maintenance.
 * Prototype and validate Ultra Ethernet capabilities for AI collective communication.
 * Provide technical input for deployment considerations and performance validation.
 * Collaborate with kernel/driver, switch, performance, and systems teams.
 * Support advanced escalations by analyzing traces and providing robust fixes.


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