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NVIDIA

Designs the chips and software that power AI

Solution Architect - Public Sector AI

Implementation & Technical Account ManagementConfirmed live in the last 24 hours
Full-timeRemote in France€69k - €152.1k

About the Job

Requirements

  • A master's degree in Computer Science, Electrical Engineering, Computer Engineering, Applied Statistics, Physics, Mathematics, another relevant engineering field, or equivalent experience.
  • At least 5 years of experience in solutions architecture, technical consulting, software development, or a closely related technical role.
  • Strong hands-on programming skills in Python and practical experience using PyTorch to build, test, and debug machine learning workflows.
  • Proven work with generative or agentic artificial intelligence, including domain adaptation or deployment of agent-based solutions.
  • Practical experience packaging and deploying artificial intelligence applications with containers and Kubernetes.
  • Ability to translate sophisticated customer requirements into clear solution architectures, working prototypes, and implementable technical plans.
  • Written, verbal, and technical presentation skills, including communicating through code, notebooks, architecture documents, and workshops.
  • Experience collaborating across customer, engineering, research, product, sales, and partner teams in an international environment.

Responsibilities

  • Translate public-sector mission goals, data constraints, and operational requirements into technical architectures for generative and agentic artificial intelligence solutions.
  • Collaborate with partners to build and demonstrate working prototypes using Python and PyTorch, then define practical paths from proof of concept to production deployment on NVIDIA accelerated computing platforms.
  • Build containerized deployment patterns using Kubernetes, including model serving, scaling, integration, and lifecycle considerations for customer environments.
  • Lead hands-on discovery sessions, technical workshops, and field trials with customer engineers and ecosystem partners, with clear success criteria and measurable technical outcomes.
  • Guide model adaptation and inference workflows for large language models, and resolve performance, compatibility, and deployment issues with partner and technical teams.
  • Create reusable notebooks, code samples, architecture guidance, and technical presentations that connect customer requirements with implementable solutions.
  • Bring structured customer and partner feedback to NVIDIA product and engineering teams to inform product requirements and remove adoption barriers.

Desired Qualifications

  • Development experience with NVIDIA GPUs, software libraries, or high-performance computing systems.
  • Applied knowledge of continuous integration and delivery, artificial intelligence model lifecycle management, and repeatable deployment pipelines for artificial intelligence systems.
  • Technical depth in one or more areas such as multimodal artificial intelligence, computer vision, edge deployment, digital twins, or data analytics.
  • Consulting or delivery experience with government customers, sovereign technology programs, or artificial intelligence startups.
  • Professional communication skills in French and English; additional Western European languages are a plus.

About the Company

NVIDIA

Designs the chips and software that power AI

NVIDIA designs the chips and software that power artificial intelligence and sells complete data center systems to cloud providers, AI labs, and other businesses, along with GeForce graphics cards for gamers. Its GPUs, chips that perform thousands of calculations at once, became the main hardware for AI after researchers used them to train the AlexNet image-recognition model in 2012. NVIDIA connects many GPUs with its own processors and networking gear into servers and rack-sized computers, and developers program them through its CUDA software. These systems bring in most of its sales, and it also makes chips for cars and robots. Jensen Huang co-founded NVIDIA in 1993, and it is based in Santa Clara, California.

Company size
10,001+
Company stage
IPO
Headquarters
Santa Clara, CA
Founded
1993

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