Senior AI Training Solutions Architect, Foundation Models

NVIDIA Corporation; Seattle (WA); On-site; USD 152,000 - 288,000; Full time

Benefits offered by this job

Equity

Benefits

Job summary

NVIDIA Corporation is seeking an experienced Senior Solutions Architect to help customers design, scale, and optimize AI training solutions using NVIDIA GPU hardware and software across cloud platforms. You will engage researchers, developers, and engineers, translating needs into scalable architectures and collaborating with product and engineering teams.

The role emphasizes foundation model pre-training and post-training, multi-GPU training, and deployment in cloud environments, with

Qualifications

• 5+ years in solutions architecture or related roles with 3+ years in large-scale AI systems
• Strong Python and PyTorch hands-on experience
• Experience with foundation model pre-training or post-training
• Experience with multi-GPU and multi-node training
• Deployment of GPU workloads in cloud environments (AWS, GCP, Azure)

Responsibilities

• Design and demonstrate scalable AI training solutions with NVIDIA hardware and software
• Lead engagements from proofs of concept to production adoption
• Develop end-to-end training workflows including reinforcement learning pipelines
• Diagnose bottlenecks across GPU compute, memory, networking, and orchestration
• Deliver technical presentations and architecture reviews for researchers and executives
• Collaborate with sales and product teams to inform roadmap

Skills

Python

PyTorch

End-to-end ML workflow

Distributed training

Education

BS/MS/PhD in CS/EE/Stats/Physics

Tools

AWS

GCP

Azure

NVIDIA NeMo Framework

Megatron Core

DeepSpeed

Docker

Kubernetes

Job description

NVIDIA Corporation is seeking an experienced Senior Solutions Architect to help customers design, scale, and optimize AI training solutions using NVIDIA GPU hardware and software across cloud platforms. You will engage researchers, developers, and engineers, translating needs into scalable architectures and collaborating with product and engineering teams.

The role emphasizes foundation model pre-training and post-training, multi-GPU training, and deployment in cloud environments, with