# Senior Performance Engineer - DGX Cloud

**Company**: NVIDIA
**Location**: Bengaluru
**Experience**: senior
**Job type**: full-time
**Category**: Engineering
**Industry**: Technology

**Apply**: https://nvidia.wd5.myworkdayjobs.com/en-US/NVIDIAExternalCareerSite/job/India-Bengaluru/Senior-Performance-Engineer---DGX-Cloud_JR2024012?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_da893284-97c

## Description

Joining NVIDIA's DGX Cloud AI Efficiency Team means advancing the performance, efficiency, and resiliency of large-scale AI workloads.

Your work will shape scalable DGX Cloud systems, turn complex measurements into prioritized engineering decisions, and continuously raise the performance and reliability of AI workloads.

**Responsibilities:**

- 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.

**Requirements:**

- 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.

**Preferred Qualifications:**

- 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.

## Skills

### Required
- C++
- Python
- performance engineering
- benchmarking
- profiling
- optimization
- operating systems
- computer architecture
- distributed systems

### Nice to have
- CUDA
- GPU computing systems
- GPU performance analysis
- PyTorch
- JAX/XLA
- large-scale AI clusters
- distributed training and inference workloads

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Source: [Apply at nvidia.wd5.myworkdayjobs.com](https://nvidia.wd5.myworkdayjobs.com/en-US/NVIDIAExternalCareerSite/job/India-Bengaluru/Senior-Performance-Engineer---DGX-Cloud_JR2024012?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)