1 day ago
Base Salary
$184k - $288k/yr
Responsibilities
- Build state-of-the-art world foundation models for Cosmos and physical AI applications.
- Analyze end-to-end performance and drive hardware-software co-design for data center infrastructure and edge deployments.
- Develop infrastructure automating multimodal data ingestion, curation, pre-training, post-training, export, quantization, and edge deployment.
- Design systems for robustness and fault tolerance.
- Engage with customers to improve Cosmos model usability and enable the broader ecosystem.
Requirements
- Master's degree in Computer Engineering, Computer Science, Electrical Engineering, or a related STEM field, or equivalent experience.
- Five years of relevant work experience.
- Expertise with large-scale parallel and distributed accelerator-based systems, performance optimization, performance modeling, and benchmarking.
- Proficiency in distributed PyTorch, Python, C, and C++.
- Strong background in computer architecture, networking, storage systems, and accelerators.
- Understanding of deep neural networks and their use in AI/ML applications and services.
- Expertise with at least one public cloud infrastructure provider, such as GCP, AWS, Azure, or OCI.
- Deep understanding of world foundation models and their applications to physical AI.
- Experience automating multimodal data ingestion and curation; dataset preparation and tokenization experience is a plus.
- Experience building autoregressive or diffusion transformer models, or frameworks for post-training, fine-tuning, and reinforcement learning algorithms.
- Understanding of inference optimization, export, quantization, and containerization.
- Familiarity with TensorFlow, JAX, Cosmos, Megatron-LM, TensorRT-LLM, or vLLM is beneficial.
- Proficiency in CUDA is beneficial.
Benefits
- Eligible for equity and benefits.
- The posting lists base salary ranges of 152,000 USD–241,500 USD for Level 3 and 184,000 USD–287,500 USD for Level 4, depending on location, experience, and comparable employee pay.
- Applications will be accepted at least until September 12, 2026.
Categories
About Nvidia
Nvidia designs and sells GPUs and accelerated computing platforms for data centers, AI/ML, graphics, gaming, and automotive, monetizing through hardware, software platforms (CUDA, AI frameworks), and systems like DGX and networking. Customers include cloud providers, enterprises, researchers, and OEMs. Founded in 1993 and headquartered in Santa Clara, it is a public company traded on NASDAQ under NVDA.