Solution Architect - Nvidia AI

Overview

Remote
$70 - $75
Contract - Independent
Contract - W2
Contract - 6 Month(s)

Skills

Amazon Web Services
Apache Spark
Artificial Intelligence
Bash
Cloud Computing
Computer Hardware
Computer Networking
Docker
Google Cloud Platform
Infrastructure Architecture
Kubernetes
Machine Learning (ML)
Machine Learning Operations (ML Ops)
Microsoft Azure
Orchestration
Python
Scripting
Terraform
Nvidia

Job Details

Solution Architect - Nvidia AI
100% remote
looking for a Solution Architect that specializes in NVidia technology. The right candidate will be able to effectively assess client environments and needs to then work with engineers and infrastructure teams to implement NVidia and AI/ML technologies. They will be helping to build out CDW's AI/ML consulting team for their clients. They will oversee the projects and engineering execution on projects, from conception to execution.
Top Candidate :-
Deep NVIDIA AI Stack Expertise
AI/ML Infrastructure Design & Deployment
Cloud & Infrastructure-as-Code (IaC)
MLOps & Model Serving
Consulting & Client-Facing Leadership
Must Haves:
3+ years of experience in AI/ML infrastructure, cloud engineering, or related consulting roles.
Strong experience with at least one major cloud platform (AWS, Azure, Google Cloud Platform), including infrastructure-as-code (Terraform, Bicep, CloudFormation).
Deep familiarity with containerization and orchestration tools (Kubernetes, Docker).
Working knowledge of distributed computing frameworks (e.g., Ray, Spark) and model serving platforms (Triton, TensorRT, ONNX).
Experience with MLOps tools like MLflow, Kubeflow, or similar.
Strong scripting/programming skills (Python, Bash, etc.).
Previous experience in a professional services or consulting role where they have overseen full cycle of project/client executions
Familiarity with AI accelerator hardware (e.g., NVIDIA GPUs, TPUs) and hybrid/edge deployments.
Hands-on experience with NVIDIA AI technologies, including CUDA, cuDNN, and the NVIDIA AI Enterprise software suite.
Knowledge of NVIDIA hardware platforms such as DGX systems and networking technologies like NVIDIA Mellanox.
Experience deploying and optimizing inference using NVIDIA Triton Inference Server.

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