Senior Performance Engineer

Details

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.

Responsibilities

• Lead all aspects of implementing performance practices in large scale infrastructure, deliver powerful tools, methodologies, and flows to validate and improve several datacenter products in parallel.
• Accelerate strategic customer deployments and ensure speed-of-light bringup and deployment of ground-breaking AI infrastructure by working hand in hand tailoring design and faster processes to customer needs.
• Own the architecting of performance design and settings of datacenter at scale products both implemented in FW and SW components to ensure velocity and scale while efficiently using resources. This involves early engagement with HW/FW/SW/platform internal and customer teams, and other groups, to build end-to-end solutions and optimize datacenter product designs.
• Supply to architecting of the implementation of server and rack level telemetry aspects, collaborate and establish continuous improvements in our design flows.
• Participate in engagements with various SW and FW (BMC/SBIOS/OS/drivers etc) teams to develop best-in-class practices and tools, analyze, debug and resolve critical firmware and software issues for the best AI workload performance at scale.
• Provide engineering solutions to enable large scale performance strategies for performance for Datacenter GPU Computing products and software stacks, ensure technical relationships with internal and external engineering teams, assisting systems engineers in building creative solutions based on NVIDIA technology.
• Be an internal reference for firmware, at scale deployment for datacenter and large-scale GPU-accelerated system solutions among the NVIDIA technical community.

Requirements

• 5+ years of experience in using accelerated computing for datacenter container computing solutions.
• Solid understanding of accelerated computing software stacks (CUDA).
• Experience using and handling modern Cloud and container-based Enterprise computing architectures.
• C/C++/Python/Bash programming/scripting experience.
• Experience with CPU architecture.
• Background with container technology and Linux based OSes.
• Experience working with engineering or academic research community supporting high performance computing or deep learning.
• Strong verbal and written communication skills as well as excellent teamwork and communication skills.
• Ability to multitask effectively in a dynamic environment.
• Action driven with strong analytical and analytical skills with a desire to be involved in multiple diverse and creative projects.
• BS in Engineering, Mathematics, Physics, or Computer Science, MS or PhD desirable (or equivalent experience).

Ways to Stand Out From the Crowd:

• Deep Learning framework skills.
• DL and graph compiling programming skills.
• Exposure to virtualization techniques, cloud platform solutions.
• Exposure to scheduling and resource management systems.
• Experience with large scale HPC environments.

NVIDIA offers highly competitive salaries and a comprehensive benefits package. The base salary range is 148,000 USD - 276,000 USD. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. You will also be eligible for equity and benefits. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer.