Senior Solutions Architect - GPU

at Nvidia
📍 Santa Clara, United States
USD 184,000-356,500 per year
SENIOR
✅ On-site

SCRAPED

Used Tools & Technologies

Not specified

Required Skills & Competences ?

Docker @ 4 Kubernetes @ 4 DevOps @ 4 GCP @ 4 MLOps @ 4 Hiring @ 4 AWS @ 4 Azure @ 4 Communication @ 7 Networking @ 7 Debugging @ 4 LLM @ 4 PyTorch @ 4 GPU @ 4

Details

Join NVIDIA's Solutions Architecture team to help bring AI solutions to strategic customers. You will collaborate with large customers to design, build, and support AI/ML and HPC software solutions at scale, acting as a primary technical point of contact and delivering end-to-end technology solutions based on NVIDIA product strategy.

Responsibilities

  • Work with large technology customers to develop and demonstrate solutions using NVIDIA software and hardware technologies.
  • Partner with Sales Account Managers and Developer Relations Managers to identify and secure opportunities for NVIDIA products and solutions.
  • Serve as the main technical point of contact for customers building complex AI infrastructure; advise on performance for large-scale LLM training and inference.
  • Run regular technical customer meetings covering project/product details, feature discussions, new technology introductions, performance advice, and debugging.
  • Collaborate with customers to build Proof of Concepts (PoCs) addressing critical business needs and support cloud service integration for NVIDIA technology on hyperscalers.
  • Analyze and develop solutions for customer performance issues across AI workloads 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 experience (performance/system/solution focus).
  • Hands-on experience building performance benchmarks for data center systems, including large-scale AI training and inference.
  • Strong understanding of systems architecture, including AI accelerators and networking, as they relate to overall application performance.
  • Effective engineering program management skills and ability to balance multiple tasks.
  • Strong written and verbal communication skills for documents, presentations, and external customer-facing engagements.

Preferred / Ways to stand out

  • Hands-on experience with deep learning frameworks such as PyTorch and JAX.
  • Experience with compilers (Triton, XLA) and NVIDIA libraries (TRTLLM, TensorRT, Nemo, NCCL, RAPIDS).
  • Familiarity with deep learning architectures and recent LLM developments.
  • Background with NVIDIA hardware and software, performance tuning, and error diagnostics.
  • Hands-on experience with GPU systems (performance testing, tuning, benchmarking).
  • Experience deploying solutions in cloud environments (AWS, GCP, Azure, OCI) and knowledge of DevOps/MLOps technologies such as Docker/containers and Kubernetes.
  • Command-line proficiency.

Compensation & Benefits

  • Base salary ranges (determined by location, experience, and internal pay parity):
    • Level 4: 184,000 USD - 287,500 USD
    • Level 5: 224,000 USD - 356,500 USD
  • Eligible for equity and benefits.

Other details

  • Applications accepted at least until October 3, 2025.
  • NVIDIA is an equal opportunity employer and values diversity in hiring and promotion practices.