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 @ 3 Kubernetes @ 3 DevOps @ 3 GCP @ 3 MLOps @ 3 AWS @ 3 Azure @ 3 Communication @ 4 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 end-to-end AI/ML and HPC software solutions at scale, focusing on performance, deployment, and integration with NVIDIA hardware and software.

Responsibilities

  • Work with major technology customers to develop and demonstrate solutions based on NVIDIA 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 primary technical point of contact for customers building complex AI infrastructure; provide guidance on performance for large-scale LLM training and inference.
  • Run regular technical customer meetings covering project/product details, feature discussions, introductions to new technologies, performance advice, and debugging.
  • Collaborate with customers to build Proof of Concepts (PoCs) that 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 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 application performance.
  • Demonstrated engineering program management skills and the ability to balance multiple tasks.
  • Excellent written and verbal communication skills for documents, presentations, and customer-facing interactions.

Preferred / Ways to stand out

  • Hands-on experience with deep learning frameworks (PyTorch, JAX, etc.), compilers (Triton, XLA, etc.), and NVIDIA libraries (TensorRT, TRTLLM, NeMo, NCCL, RAPIDS, etc.).
  • Familiarity with deep learning architectures and the latest LLM developments.
  • Background with NVIDIA hardware and software, including performance tuning and error diagnostics.
  • Hands-on experience with GPU systems including performance testing, tuning, and benchmarking.
  • Experience deploying solutions in cloud environments (AWS, GCP, Azure, OCI) and familiarity with DevOps/MLOps technologies such as Docker/containers, Kubernetes, and 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
  • Eligible for equity and additional benefits. See NVIDIA benefits for details.

Applications for this role will be accepted at least until October 3, 2025.

NVIDIA is an equal opportunity employer and is committed to fostering a diverse work environment.