2 months ago
Bengaluru, India or Hyderābād, IndiaSenior
Responsibilities
- Analyze end-to-end performance across compute, networking, storage, and software stacks for large-scale AI workloads.
- Design and execute performance studies, benchmarks, baselines, and efficiency evaluations.
- Diagnose regressions and bottlenecks using profiling, observability, and data analysis.
- Develop prioritized optimization plans and drive performance improvements through deployment.
- Partner with deep learning engineers, platform teams, and GPU architects to validate improvements.
- Communicate performance findings, tradeoffs, and recommendations to influence system and software design decisions.
Requirements
- Bachelor's degree or higher in computer science, computer engineering, or a related field, or equivalent experience.
- 12+ years of experience and strong programming skills in C++ and Python.
- Experience with performance engineering, benchmarking, profiling, and optimization of complex software or systems.
- Solid foundation in operating systems, computer architecture, and distributed systems.
- Ability to communicate technical findings, prioritize high-impact work, and build alignment across teams.
- Experience with large-scale AI clusters or distributed training and inference workloads is preferred.
- Experience with CUDA, GPU computing systems, GPU performance analysis, PyTorch, or JAX/XLA is preferred.
About Nvidia
Nvidia designs and sells GPUs and accelerated computing platforms for data centers, AI/ML, graphics, gaming, and automotive, monetizing through hardware, software platforms (CUDA, AI frameworks), and systems like DGX and networking. Customers include cloud providers, enterprises, researchers, and OEMs. Founded in 1993 and headquartered in Santa Clara, it is a public company traded on NASDAQ under NVDA.