Performance Engineering Lead for GPUs & AI

NVIDIA; Toronto; In loco; CAD 150.000 - 210.000; Tempo pieno

Descrizione del lavoro

NVIDIA is seeking a Performance Engineering Manager to lead a team of engineers focused on benchmarking, performance characterization, and data-driven optimization across CPU/GPU platforms and AI workloads. You will establish priorities, methodologies, and ensure actionable insights across engineering, product, and business units.

As a manager, you will guide complex investigations, define automation strategies, and mentor engineers while aligning performance priorities with product goals.

Competenze

• Bachelor's degree in a related technical field or equivalent experience.
• 8+ years in performance/systems/software engineering with 2+ years in leadership.

Mansioni

• Lead a team of performance engineers responsible for benchmarking, characterization, data analysis, automation, and product readiness.
• Define priorities, methodologies, and execution plans across global teams and time zones.
• Guide development of benchmarks, workloads, test methodologies, and automation for current/future platforms.
• Provide direction for investigations across GPUs, CPUs, memory, storage, networking, OS, drivers, apps, and AI workloads.
• Review data and methodologies to ensure accurate, reproducible results with rigorous analysis.
• Drive investigations of regressions and opportunities, identifying root causes and solutions.
• Translate results into clear conclusions and recommendations for product development and optimization.
• Coach engineers and evolve capabilities across platforms and workloads.

Conoscenze

Performance engineering

Leadership

Benchmarking

Automation

Data analysis

GPU/CPU systems

Scripting

Communication

Formazione

Bachelor's degree

Strumenti

Python

Linux

Descrizione del lavoro

NVIDIA is seeking a Performance Engineering Manager to lead a team of engineers focused on benchmarking, performance characterization, and data-driven optimization across CPU/GPU platforms and AI workloads. You will establish priorities, methodologies, and ensure actionable insights across engineering, product, and business units.

As a manager, you will guide complex investigations, define automation strategies, and mentor engineers while aligning performance priorities with product goals.