Manager, Performance Engineering in Toronto

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent. As an NVIDIAN, you'll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.

NVIDIA is looking for a Performance Engineering Manager to manage a team responsible for understanding, measuring, and improving performance across some of our most important computing platforms and workloads. Our Performance Engineering organization works across Consumer and Enterprise products, AI workloads, and emerging areas including Physical AI and Robotics. In this role, you will lead experienced performance engineers working at the intersection of hardware, software, applications, and system performance. You will help establish performance priorities and methodologies, guide complex technical investigations, and ensure our performance results provide clear and actionable insights to engineering, product, and business teams. This is an opportunity to develop a strong technical team while influencing the performance and direction of current and future NVIDIA products.

What you'll be doing:

• Lead, develop, and grow a team of performance engineers responsible for benchmarking, performance characterization, data analysis, automation, and product readiness.
• Define performance priorities, methodologies, and execution plans while building strong working relationships with engineering, product, and business teams across NVIDIA's global sites and time zones.
• Guide the development of benchmarks, workloads, test methodologies, and automation used to evaluate current and future NVIDIA platforms.
• Provide technical direction for complex performance investigations spanning GPUs, CPUs, memory, storage, networking, operating systems, drivers, applications, and AI workloads.
• Review performance data and methodology to ensure results are accurate, reproducible, and supported by rigorous analysis.
• Drive investigations of performance regressions and opportunities, partnering across hardware and software teams to identify root causes and potential solutions.
• Translate complex performance results into clear conclusions and recommendations that influence product development, software optimization, competitive analysis, and future performance requirements.
• Coach and develop engineers while evolving Performance Engineering capabilities across Consumer, Enterprise, Physical AI, Robotics, and other emerging platforms and workloads.

What we need to see:

• Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, or a related technical field, or equivalent experience.
• 8+ overall years of relevant experience in performance engineering, systems engineering, software engineering, computer architecture, or a related technical discipline, including 2+ years of management or technical leadership experience.
• Demonstrated experience leading and developing engineers while delivering complex technical projects across multiple teams.
• Strong understanding of computer systems and the interactions between hardware, software, operating systems, applications, and workloads.
• Experience with performance analysis, benchmarking, workload characterization, or system-level debugging.
• Strong technical judgment with the ability to guide investigations, evaluate methodology, and draw sound conclusions from complex or incomplete data.
• Familiarity with scripting or software development for automation, data analysis, or engineering tools.
• Excellent written and verbal communication skills, with demonstrated ability to collaborate effectively across organizations, geographic locations, and time zones, and communicate complex technical findings to engineering teams, business partners, and senior leaders.

Ways to stand out from the crowd:

• Hands-on performance engineering experience with the ability to mentor engineers through benchmarking, analysis, debugging, automation, and performance investigations.
• Experience with GPUs, accelerated computing, AI workloads, graphics, professional visualization, Physical AI, Robotics, or high-performance computing.
• Deep understanding of GPU architecture, computer architecture, and system-level performance bottlenecks.
• Experience developing benchmark methodologies, performance automation, or large-scale performance data and analysis pipelines.
• Experience working with preproduction hardware and translating performance analysis into product recommendations or longer-term engineering priorities.