Senior Data Center Performance Engineer
NVIDIA
Job Overview
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Job Description
About NVIDIA
NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for over 25 years. Today, NVIDIA is tapping into the unlimited potential of AI to define the next era of computing by powering GPUs that fuel computers, robots, and self-driving cars.
Role Overview: Senior Data Center Performance Engineer
This role is designed to lead performance benchmarking and optimization for NVIDIA's data center products. You will work on a range of systems from single node HGX/DGX to large multi-node NVLink domain rack architectures, ensuring industry-leading performance in accelerated computing workloads.
Responsibilities
- Design and execute comprehensive performance benchmarking strategies.
- Characterize AI training, inference, and HPC workloads at scale.
- Define, track, and report key performance indicators including throughput, latency, efficiency, and scaling.
- Build automation tools and frameworks for performance monitoring and analysis.
- Identify performance bottlenecks across compute, memory, network, and storage subsystems.
- Collaborate with architecture, hardware, software, networking, storage, and customer teams.
- Drive performance improvements through system tuning and configuration optimization.
Required Qualifications
- M.S. or Ph.D. in Computer Science, Electrical Engineering or related field; or equivalent experience.
- 8+ years in performance engineering or system architecture.
- Deep understanding of computer architecture, hardware-software interaction, and computing at scale.
- Proficiency in performance profiling tools such as Linux perf and NVIDIA Nsight Systems.
- Familiarity with GPU computing, CUDA, and HPC networking technologies.
- Programming skills in Python, C++, and shell scripting.
- Excellent analytical, problem-solving, and communication skills.
Preferred Skills & Experience
- Experience with AI/ML frameworks such as PyTorch, TensorFlow, or JAX.
- Knowledge of MPI, collective communications (NCCL), distributed training and inference.
- Experience with NVIDIA DGX, HGX platforms, containers, cloud provisioning, and scheduling tools.
- Understanding of storage systems and I/O performance optimization.
Compensation & Benefits
The base salary is determined based on location, experience, and comparable positions. In addition, you will be eligible for equity and benefits.
Application Details
Applications are accepted until February 13, 2026. This posting is for an existing vacancy.
Key skills/competency
- Benchmarking
- Optimization
- Performance
- HPC
- GPU
- Networking
- Automation
- Architecture
- Analysis
- Programming
How to Get Hired at NVIDIA
- Customize your resume: Highlight performance engineering experience and skills.
- Research NVIDIA: Understand their technologies and innovation legacy.
- Network on LinkedIn: Connect with current employees for insights.
- Prepare technically: Brush up on benchmarking and profiling tools.
- Review projects: Emphasize relevant data center and optimization projects.
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