Performance Engineering Lead for GPUs & AI in Toronto

Performance Engineering Lead for GPUs & AI in Toronto

Toronto Full-Time 148500 - 181500 $ / year (est.) On-site
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At a Glance

  • Tasks: Lead a team in benchmarking and optimizing performance for GPUs and AI workloads.
  • Company: Join NVIDIA, a leader in cutting-edge technology and innovation.
  • Benefits: Competitive salary, health benefits, and opportunities for professional growth.
  • Other info: Dynamic work environment with a focus on collaboration and mentorship.
  • Why this job: Make a real impact in the tech world by driving performance excellence.
  • Qualifications: Experience in performance engineering and strong leadership skills.

The predicted salary is between 148500 - 181500 $ per year.

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.

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Performance Engineering Lead for GPUs & AI in Toronto employer: NVIDIA

NVIDIA is an exceptional employer that fosters a culture of innovation and collaboration, making it an ideal place for Senior Architects to thrive. With a strong commitment to employee growth, you will have access to cutting-edge technology and opportunities to lead transformative projects in the dynamic field of cloud and virtualization. Located in Canada, our workplace offers a supportive environment where your contributions are valued, and you can make a meaningful impact on the future of technology.

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Contact Details:

NVIDIA Recruitment Team

We think you need these skills to ace Performance Engineering Lead for GPUs & AI in Toronto

Benchmarking
Performance Characterization
Data-Driven Optimization
CPU/GPU Platforms
AI Workloads
Team Leadership
Methodology Development