Description
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 ML software to support machine learning and gen-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 groundbreaking 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.
Mentor and support teammates through design reviews, code reviews, and collaborative development.
What we need to see:
Expert-level proficiency in Python and a track record of delivering production-quality software.
Strong experience with Porch (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.
BSc degree or equivalent experience in Computer Science, Engineering, or a related field is preferred.
5+ years of relevant software development experience
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 Porch 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.
You will also be eligible for equity and benefits. NVIDIA accepts applications on an ongoing basis.
Company
NVIDIA
Since its founding in 1993, NVIDIA (NASDAQ: NVDA) has been a pioneer in accelerated computing. The company’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined computer graphics, ignited the era of modern AI and is fueling the creation of the metaverse. NVIDIA is now a full-stack computing company with data-center-scale offerings that are reshaping industry.Simmilar jobs
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