Solutions Architect, CSP GTM

NVIDIA
Germany
Workplace: RemoteFull timeFunction: Solutions Engineering & Sales EngineeringExperience: 5+ yearsEducation: mastersSkills: ["Verbal communication","Written communication","Presentation","Self-starter","Continuous learning","Collaboration"]

Work with NVIDIA’s Worldwide Field Operations team to architect and demonstrate Physical AI solutions with hyperscaler partners. Serve as the first line of technical expertise between hyperscalers and end-customers, focusing on proof-of-concept work and performance optimization for GPU-accelerated training and inference pipelines. Collaborate with engineering, product, and sales to evangelize accelerated computing and Generative AI, while building expertise in enterprise computing architectures.

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FursaFursa
NVIDIA
NVIDIA
1 day ago

Solutions Architect, CSP GTM

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Last checked: 6 hours agoStatus: Live

Job Summary

Work with NVIDIA’s Worldwide Field Operations team to architect and demonstrate Physical AI solutions with hyperscaler partners. Serve as the first line of technical expertise between hyperscalers and end-customers, focusing on proof-of-concept work and performance optimization for GPU-accelerated training and inference pipelines. Collaborate with engineering, product, and sales to evangelize accelerated computing and Generative AI, while building expertise in enterprise computing architectures.
Location: Germany
Workplace: Remote
Employment Type: Full time
Job Function: Solutions Engineering & Sales Engineering
Seniority: Mid level

Key Responsibilities

  • •Develop and demonstrate Physical AI solutions based on hyperscalers and NVIDIA software/hardware technologies for developers.
  • •Work with customers and hyperscaler partners to understand challenges and provide solutions using NVIDIA products.
  • •Perform in-depth analysis and optimization for GPU-accelerated systems, including training and inference pipeline optimization.
  • •Partner with Engineering, Product, and Sales to plan suitable solutions, enable feature development through customer feedback, and run proof-of-concept evaluations.
  • •Build industry expertise by integrating NVIDIA technology into Enterprise Computing architectures.

Key Requirements

  • •MS/PhD (or equivalent) in Computer Science, Data Science, Electrical/Computer Engineering, Physics, Mathematics, or related engineering fields.
  • •5+ years in Solutions Architecture/Engineering in AI-related domains.
  • •Expertise in Physical AI solutions on hyperscaler infrastructure.
  • •A proven track record in machine learning, deep learning, and/or data science (academic and/or industry).
  • •Excellent English communication skills, comfortable presenting technical solutions and working across multiple teams.
Experience:5+ yearsAI-related domainsMachine learningDeep learningData science
Education:Master's
Skills:Verbal communicationWritten communicationPresentationSelf-starterContinuous learningCollaboration
Languages:English
Tech Stack:DockerKubernetesSingularity

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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