Optimize distributed AI workloads in Montreal through C++, Python, Linux, and rigorous performance benchmarking on multi-node clusters. As a System Software Engineer, you will help redefine the infrastructure layer of AI. Your focus includes communication primitives, execution primitives, and software-hardware analysis. The work supports effective execution of large-scale models across thousands of GPUs. Key Responsibilities:

Identify performance bottlenecks in distributed training workloads Investigate inference performance through software-hardware interface analysis Conduct rigorous multi-node cluster benchmarking Characterize performance across large-scale AI workloads Collaborate across the stack on foundational technology design Requirements:

Strong proficiency with C++ and Python Deep systems programming fundamentals Knowledge of memory management and concurrency Understanding of operating system internals Proficiency in Linux development environments Bring distributed systems analysis, benchmarking, and software-hardware expertise to efficient AI model execution across GPU clusters.

📌 Distributed AI Infrastructure Engineer (Winnipeg)
🏢 Delos Data
📍 Winnipeg