Presales Workstation Technologist - Advanced Compute Solutions
$147,300–$217,300 year
On-siteSant Cugat del Vallès, Catalonia, Spain
Job Summary
Lead discovery with enterprise customers to understand workloads and success criteria for AI inference acceleration, simulation, and digital twin enablement. Deliver technical workshops, whiteboard sessions, and demos tailored to GPU-accelerated platforms and advanced workstation workflows. Design end-to-end architectures integrating compute, storage, and networking, then build proof-of-concepts in customer environments while defining test plans and benchmarking performance across Linux and Windows configurations. Create reference architectures and deployment playbooks to scale field adoption, then partner with Sales, Product, and Engineering teams to share insights and influence roadmap priorities. Complete 3–6 customer workshops and 2–4 PoCs within the first year, establishing baseline benchmarks and providing actionable feedback to optimize solution packaging.
Required Qualifications
- 5+ years in presales engineering, solution architecture, advanced computing, GPU systems, workstation architecture, and/or edge AI platforms
- Bachelor's degree (or equivalent practical experience) in Engineering, Computer Science, Data Science, or related field
- Strong Linux and Windows troubleshooting and performance-tuning skills for workstation-class systems
- Ability to build and execute PoCs: define test plans, run benchmarks, interpret results, and communicate tradeoffs
- Excellent communication skills with the ability to present to both technical and executive audiences
- Location: Barcelona, UK, Spain, US and Morocco
- Travel: up to 25–40%
Desired Qualifications
- Experience with HP Advanced Compute solutions and workstation portfolio positioning
- Experience with NVIDIA Omniverse, simulation/visualization pipelines, and/or digital twin workflows
- Background in HPC, industrial edge, robotics, or automation workloads
- Certifications such as NVIDIA DLI, or cloud AI certifications (AWS/GCP/Azure), or equivalent
- Experience optimizing AI/ML inference performance and/or GPU-accelerated workstation workflows
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