Senior AI Cluster Tools Developer

Posted 4 Days Ago
Be an Early Applicant
Santa Clara, CA
Senior level
Artificial Intelligence • Hardware • Robotics • Software • Metaverse
The Role
Develop debugging and performance profiling tools for GPU clusters, collaborating with various teams to improve system performance and stability. The role includes building models for hardware and software, troubleshooting issues, and working on AI workload optimization.
Summary Generated by Built In

A key part of NVIDIA's strength is our sophisticated analysis / debugging tools that empower NVIDIA engineers to improve perf and power efficiency of our products and the running applications. We are looking for forward-thinking, hard-working, and creative people to join a multifaceted software team with high standards! This software engineering role involves developing tools for GPU Cluster users and admins.

As a member of the software development team, we will work with users from different departments like Architecture teams, Software teams. Our work brings the users intuitive, rich and accurate insight in the workload and the system, and empower them to find opportunities in software and hardware, build high level models to propose and deliver the best hardware and software to our customers, or debugging tricky failures and issues to help improve the stability of the system.

What you’ll be doing:

  • Build internal perf/power profiling and analysis tools and platform for AI workloads at cluster scale

  • Build debugging tools for common encountered problems in GPU cluster

  • Work with our users to build / calibrate perf/power models for next generation HW or system

  • Partner with architects to propose new HW features or improve existing features with real world use cases

What we need to see:

  • BS+ in Computer Science or related (or equivalent experience) and 5+ years of software development

  • Strong software design and implementation ability with Python/Go/C++

  • Good understanding of Deep Learning and AI frameworks like Pytorch, TensorFlow and etc

  • Knowledge of AI cluster job scheduling, storage management and networking management

  • Knowledge of Linux kernel

  • Excellent problem solving skills and project management skills

  • Flexibility for working in an evolving environment with changing requirements

Ways to stand out from the crowd:

  • Proven experience in GPU cluster scale continuous profiling & analysis tools/platforms

  • Solid experience in large AI job troubleshooting and failure detection/recovery

  • Skillful in Deep Learning application performance analysis and optimization

  • Knowledgeable in GPU / CPU architecture and application performance or power efficiency analysis

NVIDIA offers highly competitive salaries and a comprehensive benefits package. We have some of the most brilliant and talented people in the world working for us and, due to unprecedented growth, our world-class engineering teams are growing fast. If you're a creative and autonomous engineer with real passion for technology, we want to hear from you.

#LI-Hybrid
 

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 accepts applications on an ongoing basis.

NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

Top Skills

C++
Go
Python
The Company
HQ: Santa Clara, CA
21,960 Employees
On-site Workplace
Year Founded: 1993

What We Do

NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”

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