Senior Solutions Architect, GPU - Cloud Service Providers
at Nvidia
USD 184,000-356,500 per year
SCRAPED
Used Tools & Technologies
Not specified
Required Skills & Competences ?
Docker @ 4 Kubernetes @ 4 DevOps @ 4 GCP @ 4 MLOps @ 4 AWS @ 4 Azure @ 4 Networking @ 4 Debugging @ 4 LLM @ 4 PyTorch @ 4 GPU @ 4Details
Join our team at NVIDIA and help bring AI solutions to our largest customers. We are seeking an expert Solutions Architect to assist customers in building AI/ML and HPC software solutions at scale. As a member of our Solutions Architecture team, you will collaborate with strategic customers, providing end-to-end technology solutions and technical support based on our product strategy.
Responsibilities
- Work with tech giants to develop and demonstrate solutions based on NVIDIA’s software and hardware technologies.
- Partner with Sales Account Managers and Developer Relations Managers to identify and secure business opportunities for NVIDIA products and solutions.
- Serve as the main technical point of contact for customers engaged in the development of intricate AI infrastructure, and provide support in understanding performance aspects related to tasks like large scale LLM training and inference.
- Conduct regular technical customer meetings for project/product details, feature discussions, introductions to new technologies, performance advice, and debugging sessions.
- Collaborate with customers to build Proof of Concepts (PoCs) for solutions to address critical business needs and support cloud service integration for NVIDIA technology on hyperscalers.
- Analyze and develop solutions for customer performance issues for both AI and systems performance.
Requirements
- BS/MS/PhD in Electrical/Computer Engineering, Computer Science, Physics, or other Engineering fields or equivalent experience.
- 8+ years of engineering (performance/system/solution) experience.
- Hands-on experience building performance benchmarks for data center systems, including large scale AI training and inference.
- Understanding of systems architecture including AI accelerators and networking as it relates to the performance of an overall application.
- Effective engineering program management with the capability of balancing multiple tasks.
- Ability to communicate ideas clearly through documents, presentations, and in external customer-facing environments.
Ways to stand out
- Hands-on experience with Deep Learning frameworks (PyTorch, JAX, etc.), compilers (Triton, XLA, etc.), and NVIDIA libraries (TRTLLM, TensorRT, Nemo, NCCL, RAPIDS, etc.).
- Familiarity with deep learning architectures and the latest LLM developments.
- Background with NVIDIA hardware and software, performance tuning, and error diagnostics.
- Hands-on experience with GPU systems including performance testing, tuning, and benchmarking.
- Experience deploying solutions in cloud environments including AWS, GCP, Azure, or OCI and knowledge of DevOps/MLOps technologies such as Docker/containers, Kubernetes, data center deployments. Command line proficiency.
Compensation & Benefits
- Base salary ranges by level:
- Level 4: 184,000 USD - 287,500 USD
- Level 5: 224,000 USD - 356,500 USD
- You will also be eligible for equity and benefits (link to NVIDIA benefits provided in original posting).
Other information
- Applications for this job will be accepted at least until October 3, 2025.
- NVIDIA is committed to fostering a diverse work environment and is an equal opportunity employer.