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Solution Architect, Local Government AI

NVIDIA Corporation

Remote - Spain, Remote - GermanyRemotePosted Oct 26, 2026
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Skills named in this posting

  • Python
  • PyTorch / TensorFlow
Do you want to support our global, mission-focused government clients as they embrace AI to improve government services and increase the health, well-being, and safety of their citizens? NVIDIA is building the world’s leading AI company, one customer success at a time. Our solutions architects are key partners for our business and product teams and trusted advisors to our clients, helping them translate mission-focused goals into active AI enabled plans and actions. Specifically, we are looking for technical teammates that can help our business team develop and deploy strategies and collateral to our field teams in region and also directly support us as we educate potential clients, assist with proofs of concept, productization of workflows, and advise on successful delivery of services and solutions through our ecosystem of partners. Our team interacts regularly with colleagues, partners and customers across our global footprint. NVIDIA supports a flexible work environment where you are empowered to manage your work-life balance. Occasional international travel may be required. What you will be doing: • Empower and mentor partners, customers, and colleagues, sharing your expertise to help them grow and succeed. • Play a key role in shaping and supporting strategic plans that drive innovation at national, regional, and city levels across diverse global communities. global region. • Build engaging resources—such as presentations, blogs, and interactive notebooks—that connect business strategy with real-world government and community needs. • Collaborate with customers’ technical teams, guiding and supporting them through hands-on field trials and solution deployments. • Advocate for customer and partner needs by helping define product requirements and championing enhancements that remove barriers. • Develop and demonstrate solutions based on NVIDIA’s groundbreaking AI software and hardware technologies to customers. What we need to see: • Master's degree in Computer Science, Electrical/Computer Engineering, Applied Statistics, Physics, Mathematics, or other Engineering fields or equivalent experience. • At least five years experience in technical consulting, software development, or equivalent. At least three of those years should include delivering Computer Vision, Deep Learning, or Generative AI computing solutions or infrastructure. • Experience with at least one of the following: fine tuning or deploying computer vision models (CNNs, ViT, VLM, Gen AI); fine tuning and deploying large language models; deploying agentic and Generative AI based solutions. • Hands-on experience with Python, PyTorch and containers. • Enjoy working with multiple levels and teams across organizations (engineering/research, product, sales and marketing teams). • Effective verbal, written communications, and technical presentation skills including sharing your ideas/code clearly through blog posts and GitHub. • Self-starter with a vision for growth, dedication to continuous learning and sharing findings across the team. Ways to stand out from the crowd: • Prior work in government, AI startups, or working with digital twins. • Development experience with Kubernetes, Helm or Slurm • Experience with CICD and MLOPS technologies for building computer vision, NLP, Digital Twins or data analytics applications. • Hands-on experience in creating solutions using NVIDIA software libraries and GPUs. • Effective interpersonal and communications skills in additional languages and cultures, especially Spanish, Portuguese, French, German, Vietnamese, Thai, Bahasa, or Arabic.

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Original posting: jobs.nvidia.com

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RISC-V ecosystem

NVIDIA Corporation in the RISC-V ecosystem

RISC-V International: Premier Board

Founded in 1993, NVIDIA is an AI computing company. The company is headquartered in Santa Clara, California.

  • NVIDIA is bringing CUDA platform support to RISC-V, i.e. allowing a RISC-V CPU to host CUDA GPU applications
  • Publicly credited the RVA23 profile as the enabler: "We wouldn't have considered porting CUDA to RISC-V without it"
  • Active in RISC-V International profile/standards work and a frequent presence in RISC-V ecosystem coverage

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