At NVIDIA, we’re building the foundation for the next generation of Physical AI. Our Cosmos team is passionate about developing robust, production-grade open-source Machine Learning software to support machine learning and generative-AI research at scale. We’re looking for expert-level Python engineers who are passionate about building production-ready systems and want to make a lasting impact through open-source contributions.
If you care deeply about software craftsmanship, maintainability, and performance—and have hands-on experience building ML systems—this role is for you.
What you’ll be doing:
Develop and maintain high-quality, modular, and well-tested Python code for large-scale ML infrastructure. See https://github.com/nvidia-cosmos
Design and optimize post-training, inference, and data processing pipelines used by ground breaking ML models.
Collaborate with research and product teams to bring ML systems from prototype to production.
Contribute to open-source projects and build internal tools that enable scalable AI experimentation.
Improve performance, reliability, and observability of large distributed systems.
Support teammates through design reviews, code reviews, and collaborative development.
What we need to see:
Pursuing BS, MS or PhD degree in Computer Science, Engineering, or a related field, or equivalent experience
Strong proficiency in Python and a track record of delivering production-quality software.
Experience with PyTorch (or similar frameworks such as JAX or TensorFlow), especially in real-world applications.
Deep understanding of ML system design, training loops, data loaders, evaluation, and model serving.
Familiarity with containerization, CI/CD, and maintaining in production environments
Comfortable working with large codebases, building reusable libraries, and writing documentation and tests.
Ways to stand out in the crowd:
Contributions to open-source ML or Python infrastructure projects.
Background in scaling ML training and inference systems across GPUs as well as experience building libraries that wrap or extend PyTorch functionality.
Prior exposure to multimodal models or simulation environments (vision, language, audio).
Familiarity with NVIDIA’s GPU compute stack or high-performance computing clusters.
Experience with distributed computing tools like DDP, FSDP, ZeRO, or Ray.
Are you dedicated, upbeat and dynamic with excellent analytical ability? Are you an engineer passionate and highly motivated about solving complex problems? If so, you may be a perfect fit for NVIDIA!
You will also be eligible for equity and benefits. NVIDIA accepts applications on an ongoing basis.
NVIDIA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.
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Equity Value & Accessibility — Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
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Healthcare Strength — Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
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Retirement Support — Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.
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What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
