Senior Datacenter Performance Model Engineer
At a glance
Highlights
- Performance modeling at datacenter scale
- Collaboration with hardware and software architects
- Work on cutting‑edge AI workloads
- Focus on continuous learning and innovation
- Exposure to NVIDIA GPU and networking technologies
Heads up
- 5+ years of software development required
- Experience with NVIDIA GPUs, CUDA Programming, and Networking required
- Must work concurrently with multiple global groups
Why this role might suit you
The role provides hands‑on experience building large‑scale performance modeling tools for AI workloads, close collaboration with hardware and software architects, and exposure to cutting‑edge GPU technologies, making it appealing for engineers seeking impact in high‑performance.
Skills
About the role
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. We are looking for forward-thinking, hard-working, and creative people to join a fast-moving multifaceted software team! This software engineering role involves developing datacenter scale performance modeling and predictions tools for AI researchers running AI workloads in GPU clusters.
What you'll be doing:
Build performance modeling and prediction tools for AI workloads at Data-center scale
Develop production tools and workflows used by multiple teams both within NVIDIA and its customers.
Automate workflows including search for the most efficient configurations over millions of parameters
Partner with HW and SW 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 5+ 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 Networking
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 SW engineering experience experience in deploying SW at Dataceter scale
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
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until June 1, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
Compensation
This Software Engineer role pays $152k-$288k/yr. Within typical range for software engineer roles in United States.
Questions about this role
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