Senior Software Engineer, Cosmos Infrastructure and End to End Performance

NVIDIA; Santa Clara (CA); On-site; USD 152,000 - 288,000; Full time

Benefits offered by this job

Equity

Benefits

Job summary

NVIDIA in Santa Clara seeks a Senior Software Engineer for Cosmos Infrastructure and End to End Performance to help build the open omni-model platform and accelerate Physical AI. You will design and optimize distributed systems, work on data center and edge deployments, and collaborate with teams to enable an open ecosystem.

Requires a Masters in a STEM field, strong C/C++, Python, distributed systems experience, and CUDA expertise, with demonstrated AI/ML knowledge and CSP infra exposure.

Qualifications

• Masters in Computer Engineering, CS, EE or related STEM with equivalent experience.
• Expertise in large scale parallel and distributed accelerator-based systems.
• Expertise optimizing performance and AI workloads at scale.
• Proficiency in Distributed PyTorch; Python, C/C++. Strong background in architecture, networking, storage, accelerators.
• Understanding of DNNs and their use in AI/ML applications.
• Experience with public CSP infrastructure (GCP, AWS, Azure, OCI, ...).
• Deep understanding of World Foundation Models and their application to Physical AI.
• Experience automating multimodal data ingestion and curation; tokenization and dataset prep a plus.
• Experience building transformer models or post-training RL workflows; inference optimization (export, quantization, containerization).
• Familiarity with frameworks (TensorFlow, JAX, Cosmos, Megatron-LM, Tensort-LLM, VLLM).

Responsibilities

• Building SoTA world foundation models (like Cosmos3).
• Engage with end-to-end performance analysis and drive HW-SW codesign for data center and edge deployments.
• Engage with customers to ensure Cosmos models are easy to use and enabling the ecosystem.
• Develop infrastructure to automate data ingestion, curation, pre-training, post-training, export/quantization and edge deployment.
• Design for robustness and fault tolerance.

Skills

Distributed PyTorch

Python

C/C++

Computer Architecture

Networking

Storage systems

Accelerators

DNNs understanding

Public CSP infra

World Foundation Models

Data ingestion pipelines

Education

Master's degree in Computer Engineering, Computer Science, Electrical Engineering or related STEM

Tools

CUDA

TensorFlow

JAX

Megatron-LM

Tensort-LLM

VLLM

Cosmos

Job description

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 the NVIDIA 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

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4.

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.