Senior Performance Engineer - DGX Cloud
NVIDIA
What You'll Be Doing
- Analyze end-to-end performance of large-scale AI workloads across compute, network, storage, and software stacks.
- Design and execute rigorous performance studies to establish baselines, diagnose regressions, and quantify bottlenecks.
- Define performance and efficiency evaluation methodologies, benchmarks, and success metrics for AI workloads.
- Use profiling, observability, and data analysis to turn performance measurements into actionable optimization plans.
- Partner with deep learning engineers, platform teams, and GPU architects to validate and deliver performance improvements.
- Communicate performance findings, tradeoffs, and recommendations clearly to influence system and software design decisions.
- BS or higher degree in computer science, computer engineering, or a related field (or equivalent experience).
- 12+ years of experience in strong programming skills in C++ and Python, with the ability to build reliable analysis and automation workflows
- Solid foundation in operating systems, computer architecture, and distributed systems
- Experience with performance engineering, benchmarking, profiling, and optimization of complex software or systems
- Ability to communicate technical findings, prioritize high-impact work, and build alignment across teams
- Experience analyzing large-scale AI clusters or distributed training and inference workloads
- Experience with CUDA, GPU computing systems, and GPU performance analysis
- Hands-on experience with deep learning frameworks such as PyTorch or JAX/XLA
- Deep understanding of system-level performance analysis, workload characterization, and optimization
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