2 months ago
Remote, GermanySenior
Responsibilities
- Develop and demonstrate Physical AI solutions using hyperscaler infrastructure and NVIDIA software and hardware technologies.
- Work with customers and hyperscaler partners to understand technical challenges and provide NVIDIA-based solutions.
- Analyze and optimize performance on GPU-accelerated systems, including training and inference pipelines.
- Collaborate with Engineering, Product, Sales, and Marketing teams to address developer challenges and improve product features through customer feedback and proof-of-concept evaluations.
- Build industry expertise and contribute to integrating NVIDIA technology into enterprise computing architectures.
- Engage developers, researchers, data scientists, IT managers, technical executives, and senior leaders through technical discussions and presentations.
Requirements
- MS, PhD, or equivalent experience in Computer Science, Data Science, Electrical or Computer Engineering, Physics, Mathematics, or another engineering field.
- At least 5 years of experience in Solutions Architecture or Solutions Engineering in AI-related domains.
- Expertise with Physical AI solutions on hyperscaler infrastructure.
- Academic or industry experience in machine learning, deep learning, and/or data science.
- Strong verbal, written, listening, and technical presentation skills in English.
- Experience with large-scale distributed deep learning training, inference optimization, model compression, model compilation, or model serving is preferred.
- Experience with larger transformer-based architectures is preferred.
- Expertise in DevOps technologies such as Docker, Kubernetes, or Singularity is preferred.
Tech Stack
Categories
Solutions Engineering
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.