Senior System Software Engineer - AI Performance and Efficiency Tools

NVIDIA Gruppe; Santa Clara (CA); Hybrid; USD 184,000 - 357,000; Full time

Job summary

NVIDIA is seeking engineers to develop tools for AI researchers and software/hardware teams running AI workloads on GPU clusters. You will build profiling, analysis, and debugging tools at scale.

The role emphasizes strong C++/Python skills, experience with PyTorch/TensorFlow, and collaboration with hardware architects to deliver impactful features and improvements. Hybrid work is supported in our global setup.

Qualifications

• BS+ in Computer Science or related field (or equivalent experience) and 6+ years of software development.
• Strong skills in design, coding (C++ and Python), analytical thinking and debugging.
• Knowledge of PyTorch and TensorFlow; distributed training and inference.

Responsibilities

• Build internal profiling and analysis tools for AI workloads at large scale.
• Build debugging tools for memory, networking, and other common problems.
• Create benchmarking and simulation technologies for AI systems or GPU clusters.
• Partner with HW architects to propose new features or improve existing ones with real-world use cases.

Skills

C++

Python

Debugging

Distributed training

Problem solving

Education

BS in Computer Science or related

Tools

PyTorch

TensorFlow

Slurm

Kubernetes

CUDA

NCCL

Linux

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.

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.