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 efficient 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: Solid 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.

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📌 Distributed AI Infrastructure Engineer (Quebec City)
🏢 Delos Data
📍 Quebec City