Senior Software Engineer - AI System

at Nvidia

USD 184,000-356,500 per year

SENIOR

✅ On-site

Tech Stack
Tag name is followed by "@" symbol and proficiency level value. About proficiency levels:

1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;

3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;

7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;

10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.

AI @ 4 CI/CD @ 4 CUDA @ 7 Computer Vision @ 7 Debugging @ 7 Deep Learning @ 4 Docker @ 4 GPU @ 4 Jenkins @ 4 Linux @ 7 Profiling @ 4 Python @ 6 Software Development @ 4 TensorRT @ 4

Details

NVIDIA is seeking an experienced software engineer to help build NVIDIA AI for Media SDKs, a GPU-accelerated platform delivering AI-powered video, audio, and augmented reality capabilities for developers building media, content creation, and broadcast workflows.

The role involves developing and optimizing AI software across cloud and embedded platforms while advancing the build, validation, and delivery infrastructure behind the SDKs. You will work with C++, Linux, accelerated inference, and software delivery automation, collaborating with algorithm, platform, infrastructure, and QA teams to deliver efficient and reliable software on NVIDIA hardware.

Responsibilities

Build efficient, low-latency software for AI media workloads across cloud and embedded platforms.
Optimize and deploy AI models and software stacks on embedded processors and NVIDIA GPU platforms.
Profile AI workloads to improve performance, power consumption, and memory usage.
Develop and maintain cross-platform CI/CD, packaging, and test systems.
Collaborate across NVIDIA to bring new hardware capabilities and platform software to AI media applications.
Drive projects from design through validated release, with clear milestones, documentation, and reliable handoffs.

Requirements

Strong C++ and CUDA programming, system design, debugging, and software engineering skills.
Strong Linux development expertise, including toolchains, dependency management, scripting, and troubleshooting.
Bachelor's or master's degree, or equivalent experience, with 8 or more years of relevant systems software development experience.
Experience with CI/CD systems such as Jenkins or GitLab CI, including automated build, test, and packaging workflows.
Experience with Docker-based development and build environments.
Strong background in computer vision, graphics, and linear algebra.
Ability to work independently, define project scopes, communicate risks, and drive work through completion.
Experience shipping production SDKs and developer libraries.
Proficiency in AI-driven development best practices and agentic engineering workflows.

Preferred Qualifications

TensorRT inference integration or optimization experience.
Experience building and deploying software or AI models on embedded platforms, particularly ARM-based systems.
Experience optimizing deep learning system performance, including latency analysis, profiling, and tuning of AI workloads.
Expertise in image and video processing in GPU-accelerated media applications.
Proficiency with Python and shell scripting for development and infrastructure automation.