Senior Software Engineer, Cosmos Infrastructure and End to End Performance

Nvidia

Confirmed live yesterday High trust

Quick summary

Work type
On-site
Location
Santa Clara, CA
Salary
$152,000–$241,500 / yr
Posted
3 days ago
Freshness
Confirmed live yesterday

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $167k
This role $197k
$105k most similar roles pay here $256k

This role pays more than 77% of similar roles. Most pay $144,350–$190,000 — the shaded band above. At the midpoint, this role pays about $197k versus about $167k for comparable roles.

Based on 240 similar postings.

Employer

About Nvidia

Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing

Nvidia currently has 896 open roles on FindRole.

Listed pay typically runs $184,000–$287,500 across 876 roles with salary data.

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View all roles at Nvidia

At a glance

TL;DR · Senior Software Engineer, Cosmos Infrastructure and End to End Performance

As a Senior Software Engineer, Cosmos Infrastructure and End to End Performance, you will join the team building the foundational platform for Physical AI ecosystem enablement. You will build state-of-the-art world foundation models while driving end-to-end performance analysis and hardware-software codesign for data center and edge deployments. Your daily work involves developing infrastructure to automate data ingestion, curation, pre-training, post-training, export, quantization, and deployment. You will solve complex problems regarding robust systems and the integration of world generation with physical reasoning. The role requires expertise in large-scale parallel and distributed accelerator-based systems, performance modeling, and benchmarking. Required skills include Python, C/C++, Distributed PyTorch, and CUDA. You must possess a deep understanding of computer architecture, networking, storage systems, DNNs, transformer models, and multimodal data curation to support the development of generative world foundation models for physical AI applications.

What does a Software Engineer earn in California?

Median $214000 from 775 postings across 63 companies.

See salary data

What you'll do

  • Build state-of-the-art world foundation models like Cosmos3.
  • Drive end-to-end performance analysis and hardware-software codesign for data center and edge deployments.
  • Develop infrastructure to automate data ingestion, curation, pre-training, and post-training processes.
  • Optimize model deployment through export, quantization, and containerization.
  • Design systems for robustness and fault tolerance in large-scale distributed environments.
  • Engage with customers to ensure models are accessible and usable for the ecosystem.

What we're looking for

  • A Master's degree in Computer Engineering, Computer Science, Electrical Engineering, or a related STEM field or equivalent experience.
  • 5 years of relevant work experience.
  • Expertise in large-scale parallel and distributed accelerator-based systems.
  • Experience optimizing performance and AI workloads on large-scale systems.
  • Proficiency in Distributed PyTorch, Python, and C/C++.
  • Strong background in Computer Architecture, Networking, Storage systems, and Accelerators.
  • Understanding of DNNs and World Foundation Models applied to Physical AI.
  • Expertise with at least one public CSP infrastructure (GCP, AWS, Azure, or OCI).
  • Experience developing infrastructure for multimodal data ingestion and curation.
  • Experience driving tokenization and dataset preparation (preferred).
  • Prior experience building transformer models or driving post-training, fine-tuning, and RL algorithms (preferred).
  • Understanding of inference optimization including export, quantization, and containerization.
  • Familiarity with AI frameworks like TensorFlow, JAX, Megatron-LM, Tensort-LLM, or VLLM (preferred).
  • Proficiency in CUDA (preferred).

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