multimodal AI / computer vision / edge deployment / digital twins / data analytics
French
About NVIDIA
NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years.
It’s a unique legacy of innovation that’s fueled by great technology—and amazing people.
Today, we’re tapping into the unlimited potential of AI to define the next era of computing.
An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world.
Doing what’s never been done before takes vision, innovation, and the world’s best talent.
As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work.
Come join the team and see how you can make a lasting impact on the world.
At NVIDIA, we are helping public-sector organizations use accelerated computing and artificial intelligence (AI) to improve government services, research and national capabilities.
The Global Public Sector team is seeking a Solutions Architect based in France to turn sovereign AI priorities into scalable technical solutions.
As you plan your future, see what we can offer to you and your family www.nvidiabenefits.com/
Responsibilities
This hands-on role collaborates with solutions partners, government entities, research organizations, integrators and NVIDIA engineering and product teams to develop architectures, build proofs of concept and move validated workflows toward production.
The work spans generative and agentic AI, model adaptation, GPU-accelerated inference, containerized platforms and machine learning operations.
Travel within France and occasionally across Europe may be required for customer engagements.
Translate public-sector mission goals, data constraints and operational requirements into technical architectures for generative and agentic AI 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.
We 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, then solve performance, compatibility and deployment issues with partner and technical teams.
We 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.
Requirements
Master’s degree in Computer Science, Electrical Engineering, Computer Engineering, Applied Statistics, Physics, Mathematics or another relevant engineering field or equivalent experience.
5 or more years of meaningful 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 AI, including domain adaptation or deployment of agent-based solutions.
Ability to turn sophisticated customer requirements into clear solution architectures, working prototypes, and ready-to-implement technical plans.
Clear written, verbal and technical presentation skills, including the ability to communicate through code, notebooks, architecture documents and workshops.
Proven teamwork across customer, engineering, research, product, sales and partner teams in an international environment.
Ways to stand out from the crowd: Development experience with NVIDIA GPUs, software libraries or high-performance computing systems.
Preferred
Practical experience packaging and deploying AI applications with containers and Kubernetes.
Applied knowledge of continuous integration and delivery, AI model lifecycle management, and repeatable deployment pipelines for AI systems.
Technical depth in one or more areas such as multimodal AI, computer vision, edge deployment, digital twins or data analytics.
Consulting or delivery experience with government customers, sovereign technology programs or AI startups.
Professional communication skills in French and English; additional Western European languages are a plus.
Benefits
Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package.
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