Senior AI Workload Performance Engineer

NVIDIA; Schweiz; Vor Ort; CHF 150.000 - 210.000; Vollzeit

Zusammenfassung

NVIDIA is seeking a Performance Engineer to characterize workloads, establish performance baselines, diagnose bottlenecks, and drive optimizations across DGX Cloud AI efficiency efforts. You will shape scalable systems, translate measurements into engineering actions, and raise AI workload performance and reliability.

You will partner with deep learning engineers, platform teams, and GPU architects to validate improvements and communicate findings that influence design decisions.

Qualifikationen

• BS or higher degree in computer science, computer engineering, or a related field, with 12+ years of experience.
• Strong programming skills in C++ and Python, with the ability to build reliable analysis and automation workflows.
• Solid foundation in operating systems, computer architecture, and distributed systems.
• Experience with performance engineering, benchmarking, profiling, and optimization of complex software or systems.
• Ability to communicate technical findings, prioritize high-impact work, and build alignment across teams.

Aufgaben

• Analyze end-to-end performance of large-scale AI workloads across compute, network, storage, and software stacks.
• Design and execute rigorous performance studies to establish baselines, diagnose regressions, and quantify bottlenecks.
• Define performance and efficiency evaluation methodologies, benchmarks, and success metrics for AI workloads.
• Use profiling, observability, and data analysis to turn performance measurements into actionable optimization plans.
• Partner with deep learning engineers, platform teams, and GPU architects to validate and deliver performance improvements.
• Communicate performance findings, tradeoffs, and recommendations clearly to influence system and software design decisions.

Kenntnisse

C++

Python

Performance profiling

Distributed systems

Communication

Ausbildung

BS or higher in CS/CE

Jobbeschreibung

NVIDIA is seeking a Performance Engineer to characterize workloads, establish performance baselines, diagnose bottlenecks, and drive optimizations across DGX Cloud AI efficiency efforts. You will shape scalable systems, translate measurements into engineering actions, and raise AI workload performance and reliability.

You will partner with deep learning engineers, platform teams, and GPU architects to validate improvements and communicate findings that influence design decisions.