Senior Solutions Architect, GPU - Cloud Service Providers

at Nvidia
📍 Santa Clara, United States
USD 148,000-287,500 per year
SENIOR
✅ On-site

SCRAPED

Used Tools & Technologies

Not specified

Required Skills & Competences ?

Docker @ 3 Kubernetes @ 3 DevOps @ 3 GCP @ 3 MLOps @ 3 Hiring @ 4 AWS @ 3 Azure @ 3 Communication @ 7 Networking @ 4 Debugging @ 4 LLM @ 4 PyTorch @ 4 GPU @ 4

Details

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 developing complex AI infrastructure; provide guidance on performance for large-scale LLM training and inference.
  • Conduct 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) addressing 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.
  • 3+ years of engineering experience (performance/system/solution engineering).
  • 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 overall application performance.
  • Effective engineering program management skills with the ability to balance multiple tasks.
  • Strong written and verbal communication skills for documents, presentations, and external customer-facing interactions.

Ways to stand out

  • Hands-on experience with deep learning frameworks such as PyTorch and JAX.
  • Experience with compilers and related tooling (Triton, XLA).
  • Familiarity with NVIDIA libraries and toolkits (TRTLLM, TensorRT, NeMo, NCCL, RAPIDS, etc.).
  • Knowledge of deep learning architectures and the latest LLM developments.
  • Background with NVIDIA hardware/software, 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 is expected.

Compensation & Benefits

  • Base salary ranges by level:
    • Level 3: 148,000 USD - 235,750 USD
    • Level 4: 184,000 USD - 287,500 USD
  • You will also be eligible for equity and benefits (see NVIDIA benefits page).

Application deadline

Applications for this job will be accepted at least until July 29, 2025.

Equal opportunity

NVIDIA is committed to fostering a diverse work environment and is an equal opportunity employer. We do not discriminate in hiring or promotion practices on the basis of protected characteristics.