Apply

Ready to go for it?

AI Apply speeds things up—apply directly if you prefer.

FREE ACCESS
5,000–10,000 jobs/day
JobTailor Logo

See all jobs on JobTailor

Search thousands of fresh jobs every day.

Discover
  • Fresh listings
  • Fast filters
  • No subscription required
Create a free account and start exploring right away.
NVIDIA

Solutions Architect, AI and ML

NVIDIA

Solutions Architect building NVIDIA AI/ML cloud solutions for enterprise customers. Deploying GPU-powered machine learning systems and creating customer proofs of concept across AWS, GCP, and Azure.

Posted 8/10/2026full-timeRedmond • California, Washington • 🇺🇸 United StatesMid-LevelSenior💰 $124,000 - $241,500 per yearWebsite

Core Competencies

Role fit
Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in building and deploying AI/ML solutions using NVIDIA technologies on cloud platforms, with a strong foundation in Deep Learning and Machine Learning. Capable of engaging with technical stakeholders to drive business solutions and deliver impactful presentations.

Highest-signal resume keywords
Solutions Engineering ExperienceDeep Learning and Machine LearningTensorFlow or PyTorchCloud Computing EnvironmentsNVIDIA GPUs and SDKs

ATS Keywords

Tailor your resume
Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills
Deep LearningMachine LearningTensorFlowPyTorchCUDAScripting Language (Python)Programming and Debugging SkillsCloud Computing (AWS, GCP, Azure)DevOps/ML Ops TechnologiesParallel Programming
Soft Skills
Communication SkillsTechnical Presentation Skills
Tools & Technologies
NVIDIA Hardware and SoftwareDocker/ContainersKubernetesData Center Deployments
Certifications & Qualifications
AWS Professional Solution Architect CertificationGCP Professional Solution Architect CertificationAzure Professional Solution Architect Certification
Industry Keywords
AI SolutionsML SolutionsCloud Service ProvidersTechnical Customer EngagementBusiness Strategy

Tech Stack

Tools & technologies
AWSAzureCloudDockerGoogle Cloud PlatformKubernetesPythonPyTorchTensorflow

About the role

Key responsibilities & impact
  • Work with Cloud Service Providers to develop and demonstrate solutions based on NVIDIA’s ML/DL and data science software and hardware technologies
  • Build and deploy AI/ML solutions at scale using NVIDIA's AI software on cloud-based GPU platforms
  • Build custom proofs of concept addressing customers’ critical business needs with NVIDIA hardware and software
  • Partner with Sales Account Managers or Developer Relations Managers to identify and secure new business opportunities for NVIDIA products and solutions
  • Prepare and deliver technical content to customers, including presentations and workshops
  • Conduct regular technical customer meetings covering project and product roadmaps, feature discussions, and new technologies
  • Establish close technical ties with customers to facilitate rapid resolution of customer issues
  • Engage directly with developers, researchers, and data scientists at strategic technology customers
  • Work with business and engineering teams on product strategy
  • Drive end-to-end technology solutions based on customer business needs

Requirements

What you’ll need
  • 3+ years of Solutions Engineering or similar Sales Engineering experience, or equivalent experience
  • 3+ years of work-related experience in Deep Learning and Machine Learning
  • Experience with TensorFlow or PyTorch, GPU, and CUDA
  • BS, MS, or PhD in Electrical/Computer Engineering, Computer Science, Statistics, Physics, or another Engineering field, or equivalent experience
  • Track record of deploying solutions in cloud computing environments, including AWS, GCP, or Azure
  • Knowledge of DevOps/ML Ops technologies such as Docker/containers, Kubernetes, and data center deployments
  • Ability to use at least one scripting language, such as Python
  • Good programming and debugging skills
  • Ability to communicate ideas and code clearly through documents and presentations
  • AWS, GCP, or Azure Professional Solution Architect Certification is a differentiator
  • Hands-on experience with NVIDIA GPUs and SDKs such as CUDA, RAPIDS, or Triton is a differentiator
  • System-level experience with GPU-based systems is a differentiator
  • Experience with Deep Learning at scale is a differentiator
  • Familiarity with parallel programming and distributed computing platforms is a differentiator

Benefits

Comp & perks
  • Equity
  • Benefits
  • Occasional travel for local on-site customer visits and industry events