Job description

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 AI researchers and SW/HW teams running AI workload in GPU cluster. 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 performance and efficiency of the system. What you’ll be doing: • Build internal profiling and analysis tools for AI workloads at large scale • Build debugging tools for common encountered problems like memory or networking • Create benchmarking and simulation technologies for AI system or GPU cluster • Partner with HW architects to propose new 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 6+ years of software development • Strong software skills in design, coding (C++ and Python), analytical, and debugging • Good understanding of Deep Learning frameworks like PyTorch and TensorFlow, distributed training and inference. • Knowledge of GPU cluster job scheduling (Slurm or Kubernetes), storage and networking • Experience with NVIDIA GPUs, CUDA Programming and NCCL • Motivated self-starter with strong problem-solving skills and customer-facing communication skills • Passion for continuous learning. Ability to work concurrently with multiple global groups Ways to stand out from the crowd: • Proven experience in GPU cluster scale continuous profiling & analysis tools/platforms • Solid experience in large AI job performance analysis for training/inference workload • Knowledge of Linux device drivers and/or compiler implementation • Knowledge of GPU and/or CPU architecture and general computer architecture principles #LI-Hybrid Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 10, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. 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.

Requirements

Must-haves

Build internal profiling and analysis tools for AI workloads at large scale
Build debugging tools for common encountered problems like memory or networking
Create benchmarking and simulation technologies for AI system or GPU cluster
Partner with HW architects to propose new features or improve existing features with real world use cases
BS+ in Computer Science or related (or equivalent experience) and 6+ years of software development
Strong software skills in design, coding (C++ and Python), analytical, and debugging
Good understanding of Deep Learning frameworks like PyTorch and TensorFlow, distributed training and inference.
Knowledge of GPU cluster job scheduling (Slurm or Kubernetes), storage and networking
Experience with NVIDIA GPUs, CUDA Programming and NCCL
Motivated self-starter with strong problem-solving skills and customer-facing communication skills
Passion for continuous learning. Ability to work concurrently with multiple global groups
Proven experience in GPU cluster scale continuous profiling & analysis tools/platforms
Solid experience in large AI job performance analysis for training/inference workload
Knowledge of Linux device drivers and/or compiler implementation
Knowledge of GPU and/or CPU architecture and general computer architecture principles
You will also be eligible for equity and benefits .
Applications for this job will be accepted at least until May 10, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aipythonkubernetes

Platform: eightfold
Effort: medium