Senior Software Engineer, Cosmos Infrastructure and End to End Performance
We're now looking for a Senior Software Engineer, Cosmos Infrastructure and End to End Performance! NVIDIA Cosmos is an open omni-model platform of generative world foundation models (WFMs) designed to accelerate physical AI. By combining world generation, physical reasoning, and action generation into unified systems, Cosmos helps developers simulate physical environments and train robots, autonomous vehicles, and smart spaces. You can explore the project via theNVIDIA Cosmos GitHub or look up releases on Hugging Face.
Our team's mission is to build the foundational platform for Physical AI ecosystem enablement, empowering developers to create, train, evaluate, and deploy Physical AI systems through open frontier models and open SOTA training and data curation frameworks.
What you will be doing:
Building SoTA, World foundation models (https://arxiv.org/pdf/2606.02800) (like Cosmos3);
Engage with driving end to end performance analysis and drive HW-SW codesign for both the data center infrastructure and Edge deployments
Engage with customers to ensure the Cosmos models are easy to use and enabling the ecosystem;
Develop infrastructure to improve and automate the entire process of data ingestion, curation, pre-training, post-training, Export/quantization and deployment on the edge;
Design for robustness and fault tolerance.
What we need to see:
A Masters in Computer Engineering, Computer Science, Electrical Engineering or related STEM degree or equivalent experience. 5 years of relevant work experience
Expertise in working with large scale parallel and distributed accelerator-based system systems
Expertise optimizing performance and AI workloads on large scale systems. Experience with performance modeling and benchmarking at scale
Proficiency in Distributed PyTorch; Python, C/C++. A strong background in Computer Architecture, Networking, Storage systems, Accelerators
Understanding of DNNs and their use in emerging AI/ML applications and services
Expertise with at least one of public CSP infrastructure (GCP, AWS, Azure, OCI, …)
A deep understanding of World Foundation Models and their application to Physical AI
Experience developing infrastructure to automate multimodal data ingestion and curation. Experience driving tokenization and data set preparation is a plus.
Prior experience building transformer models (autoregressive and diffusion) or building the framework for and driving Post training - fine tuning and RL algorithms
Understanding of how to optimize for inference - export, quantization and containerization
Ways to stand out from the crowd:
Familiarity with popular AI frameworks (TensorFlow, JAX, Cosmos, Megatron-LM, Tensort-LLM, VLLM) among others.
Proficiency in CUDA
Very high intellectual curiosity; Confidence to dig in as needed; Not afraid of confronting complexity; Able to pick up new areas quickly with excellent interpersonal skills
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until September 12, 2026.This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.