Senior Solutions Architect, Higher Education and Research, Multimodal and Physical AI

NVIDIA
Zurich
Workplace: OnsiteFull timeFunction: Solutions Engineering & Sales EngineeringEducation: mastersSkills: ["Collaboration","Communication","Analytical","Self-motivated","Organization"]

Partner with research labs, university faculty, and researchers as a trusted technical advisor to drive NVIDIA adoption at supercomputing scale. Integrate NVIDIA frameworks, libraries, and core software into multimodal and Physical AI research, accelerating high-impact workloads and translating needs into prototypes. Deliver trainings, workshops, lectures, and demos across NVIDIA platforms, while maintaining deep domain expertise in GPUs, CPUs, networking, and software.

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FursaFursa
NVIDIA
NVIDIA
2 days ago

Senior Solutions Architect, Higher Education and Research, Multimodal and Physical AI

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Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 13 hours agoStatus: Live

Job Summary

Partner with research labs, university faculty, and researchers as a trusted technical advisor to drive NVIDIA adoption at supercomputing scale. Integrate NVIDIA frameworks, libraries, and core software into multimodal and Physical AI research, accelerating high-impact workloads and translating needs into prototypes. Deliver trainings, workshops, lectures, and demos across NVIDIA platforms, while maintaining deep domain expertise in GPUs, CPUs, networking, and software.
Location: Zurich
Workplace: Onsite
Employment Type: Full time
Job Function: Solutions Engineering & Sales Engineering
Seniority: Mid level

Key Responsibilities

  • •Partner directly with research labs, researchers, and university faculty to understand scientific goals and drive joint research at supercomputing scale.
  • •Identify and accelerate high-impact workloads by integrating NVIDIA frameworks, libraries, and software stack into research projects.
  • •Advocate for accelerated computing, robotics, Multimodal AI, and Physical AI; deliver trainings, workshops, lectures, demonstrations, and mentor power users.
  • •Track emerging research trends and convert gaps between researcher needs and NVIDIA offerings into prototypical solutions and feedback for NVIDIA Engineering.
  • •Maintain deep domain expertise while staying versatile across NVIDIA platforms including GPUs, CPUs, networking, and software.
Travel: Medium travel

Key Requirements

  • •Graduate degree in a STEM discipline or equivalent experience.
  • •5+ years across the multimodal and world model lifecycle on multi-node GPU systems, including data curation, pre-/post-training, evaluation, and efficient inference.
  • •Strong collaboration and communication skills with academic and research stakeholders, and the ability to explain complex ideas to expert and non-expert audiences.
  • •Action-oriented, analytical, self-motivated, and organized for a heavily multi-tasked environment.
  • •Fluency in English (oral and written) and comfort working in Python.
Experience:Multimodal AIWorld modelsAccelerated computingRoboticsSupercomputingAcademic research
Education:Master's
Skills:CollaborationCommunicationAnalyticalSelf-motivatedOrganization
Languages:English
Tech Stack:PythonCUDACUDA-XCosmosNeMo FrameworkMegatronIsaac robotics platformNuRecTensorRTNIMMONAI

Company Brief

NVIDIA
Designs and manufactures GPUs, AI accelerators, and system-on-chip products for gaming, data centers, professional visualization, and automotive markets, enabling advanced graphics, AI, and high-performance computing solutions worldwide.
Industry: Electronics Manufacturing
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Public Company
Valuation: Public Company (Market Cap in USD)
Funding: IPO / Publicly Listed
Headquarters: Santa Clara, United States
Founded: 1993
Glassdoor
Glassdoor: 4.3
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