Senior GPU AI Solutions Architect — GenAI & HPC

NVIDIA; New York (NY); On-site; USD 184,000 - 288,000; Full time

Benefits offered by this job

Equity

Benefits

Job summary

NVIDIA is seeking an experienced Solutions Architect to bridge design and deployment of large-scale AI/HPC GPU infrastructure. You will drive adoption of NVIDIA GPU solutions by partnering with customers, engineers, and partners across the full lifecycle.

Ideal candidates have 10+ years in solution engineering, strong Python/DL framework skills (PyTorch, TensorFlow), and hands-on experience with clustered cloud architectures.

Qualifications

• BS/MS/PhD in Electrical/Computer Engineering, Computer Science, Physics, Mathematics or related field.
• 10+ years in Solution Engineering or similar roles with partners/customers.
• Experience building large-scale cluster environments and distributed cloud architectures.
• Strong programming and deep learning framework skills (Python, PyTorch, TensorFlow).
• Proven ability to drive multi-disciplinary technical engagements and cross-functional collaboration.

Responsibilities

• Collaborate with NVIDIA Cloud Partners to deliver hardware/software solutions.
• Align strategies with SAs, Account Managers, Eng, Product, and leadership to drive opportunities.
• Lead technical design, development, deployment, and production support for GPU Cloud infrastructure.

Skills

Python

Deep Learning

Distributed systems

Presentation

Customer-facing

Time management

Growth mindset

Education

BS/MS/PhD in Electrical/Computer Engineering, CS, Physics, Mathematics

Tools

NVIDIA CUDA-X

TensorRT

NVIDIA Triton

NVIDIA NeMo

PyTorch

TensorFlow

SLURM

Kubernetes

NCCL

Job description

NVIDIA is seeking an experienced Solutions Architect to bridge design and deployment of large-scale AI/HPC GPU infrastructure. You will drive adoption of NVIDIA GPU solutions by partnering with customers, engineers, and partners across the full lifecycle.

Ideal candidates have 10+ years in solution engineering, strong Python/DL framework skills (PyTorch, TensorFlow), and hands-on experience with clustered cloud architectures.