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Solutions Architect, AI and ML

LinkedIn NVIDIA Redmond, WA
Not Applicable Posted April 2, 2026 2 variants Job link
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Requirements
  • 3+ years of Solutions Engineering (or similar Sales Engineering roles) or equivalent experience
  • 3+ years of work-related experience in Deep Learning and Machine Learning, including deep learning frameworks TensorFlow or PyTorch, GPU, and CUDA experience extremely helpful.
  • Established 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, data center deployments
  • Ability to use at least one scripting language (i.e., Python)
  • Good programming and debugging skills
  • Ability to communicate your ideas/code clearly through documents, presentation etc.
  • System-level experience specifically GPU-based systems
  • Experience with Deep Learning at scale
  • Familiarity with parallel programming and distributed computing platforms
  • We make extensive use of conferencing tools, but occasional travel is required for local on-site visit to customers and industry events.
Preferred Skills
  • AWS, GCP or Azure Professional Solution Architect Certification.
  • Hands-on experience with NVIDIA GPUs and SDKs (e.g.
  • CUDA, RAPIDS, Triton etc.)
  • System-level experience specifically GPU-based systems
  • Experience with Deep Learning at scale
  • Familiarity with parallel programming and distributed computing platforms
Education
  • (Not required) – BS/MS/PhD in Electrical/Computer Engineering, Computer Science, Statistics, Physics, or other Engineering fields or equivalent experience.
  • (Not required) – AWS, GCP or Azure Professional Solution Architect Certification.