Senior AI & GPU Cloud Solutions Architect

NVIDIA Corporation; Santa Clara (CA); On-site; USD 184,000 - 288,000; Full time

Job summary

NVIDIA seeks an experienced Solutions Architect to be a trusted technical advisor, bridging design to deployment of large-scale AI/HPC GPU infrastructure. You will collaborate with partners and internal teams to deliver Nvidia hardware and software solutions for production-grade GPU cloud workloads.

You will own end-to-end technical engagements, conduct regular customer reviews, and help customers deploy DL models using frameworks like PyTorch and TensorFlow.

Qualifications

• 10+ years of Solution Engineering or similar roles with partners/customers.
• Experience crafting and deploying large-scale cluster environments and distributed cloud architectures.
• Strong programming fundamentals with Python and DL frameworks (PyTorch, TensorFlow).
• Ability to own and drive complex multi-disciplinary technical engagements across the customer lifecycle.
• Excellent presentation, communication and collaboration skills.

Responsibilities

• Collaborate with NVIDIA Cloud Partners to deliver innovative hardware and software solutions.
• Partner with SAs, Account Managers, Engineering and Product to align on strategies and opportunities.
• Serve as the primary technical driver during design, development, deployment, and production of GPU Cloud infra and apps.
• Lead PoCs and technical workshops, and produce reference architectures and tutorials.

Skills

Deep Learning

Python

PyTorch

TensorFlow

Cloud architectures

Distributed systems

MLOps

GPU hardware

CUDA

Solution Architecture

Stakeholder management

Enterprise customer engagement

Education

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

Tools

NCCL

Kubernetes

SLURM

TensorRT

NeMo

DCGM

Job description

NVIDIA seeks an experienced Solutions Architect to be a trusted technical advisor, bridging design to deployment of large-scale AI/HPC GPU infrastructure. You will collaborate with partners and internal teams to deliver Nvidia hardware and software solutions for production-grade GPU cloud workloads.

You will own end-to-end technical engagements, conduct regular customer reviews, and help customers deploy DL models using frameworks like PyTorch and TensorFlow.