Presales Workstation Technologist - HPI + NVIDIA

MarketStar•Ogden, UT

12d•$120,000 - $130,000•Remote

About The Position

We are seeking a highly skilled Workstation Technologist to serve as subject-matter expert across the complete HP Product portfolio, utilizing the NVIDIA Edge product portfolio, including edge AI workstations, GPU-accelerated platforms, RTX-powered systems, and enterprise edge infrastructure solutions. This role bridges advanced compute, AI acceleration, and edge-to-cloud architectures, enabling customers to harness NVIDIA technologies for high-performance, real-time, mission-critical workloads. The ideal candidate is a hands-on technologist with deep knowledge of NVIDIA GPUs, CUDA, TensorRT, Omniverse, AI frameworks, and edge system architecture, capable of guiding customers, partners, and internal engineering teams through the design, deployment, and optimization of intelligent edge solution

Requirements

5+ years in advanced computing, GPU systems, workstation architecture, or edge AI platforms.
Bachelor’s degree or equivalent in engineering, Computer Science, or Data Science
Strong understanding of NVIDIA GPU architecture (RTX, Ada, Ampere, Hopper).
Proficiency with CUDA, TensorRT, ONNX Runtime, and AI frameworks.
Strong Linux/Windows workstation performance tuning skills.
Experience with containerization (Docker, Kubernetes, GPU Operator).
Experience with AI/ML workload optimization or industrial edge deployments.
Excellent communication skills across technical and executive audiences.

Nice To Haves

Experience with NVIDIA Jetson, Omniverse, AI Enterprise, or NIM microservices.
Background in HPC, robotics, industrial automation, or digital twin workloads.
Certifications such as NVIDIA DLI, AWS/GCP/Azure AI, or equivalent.

Responsibilities

Serve as the primary technical authority for the entire NVIDIA Edge product line.
Provide architecture guidance around AI inference, simulation, visualization, digital twins, and advanced workstation workflows.
Design end-to-end edge computing architectures integrating GPU-accelerated compute, storage, networking, and edge-to-cloud orchestration.
Evaluate workload requirements across AI, ML, HPC, visualization, robotics, automation, and industrial edge.
Conduct performance modeling and benchmarking.
Engage with enterprise customers to assess use cases, define requirements, and architect NVIDIA-based solutions.
Deliver technical workshops, whiteboard sessions, and demos.
Support deployment, tuning, and optimization of NVIDIA Edge platforms.
Create documentation, reference architectures, and playbooks.
Partner with cross‑functional teams to align product strategy and share field insights.
Other applicable duties as assigned.