Top Artificial Intelligence Jobs in Paris

The role involves leading AI research in finance, developing innovative algorithms, collaborating with a multidisciplinary team, and driving research projects autonomously.

Lead research and innovation projects in Material Science using AI/ML, identify problems, develop solutions, and collaborate with multidisciplinary teams.

The role involves developing features for GitLab's AI-powered platform, advocating for quality improvements, and collaborating within a remote team.

The Head of Operations & AI Enablement will diagnose operational issues, design solutions, and enhance efficiency using AI/ML, partnering with various teams to drive improvements.

As an AI & Data Software Engineer, you'll develop web applications, integrate AI features, and collaborate with teams to optimize workflows. You will write code, build APIs, and advocate for AI advancements while maintaining high development standards.

Develop computer vision models for object recognition and video understanding while evaluating and improving their performance for real-world applications.

Lead a team of AI Product Designers to shape the future of AI-powered developer tools, managing design strategy, user research, and cross-functional collaboration.

Drive independent, high-impact research on frontier AI topics, publish findings, collaborate widely, and mentor new researchers in the field.

The AI Software Engineer - Agents will develop AI systems, mentor junior engineers, and optimize AI solutions for performance and scalability in a collaborative environment.

The role involves architecting and designing scalable AI systems for payment processing, collaborating with cross-functional teams, and integrating innovative AI technologies.

The AI Manager will lead a team in developing AI solutions, focusing on GenAI and driving technical decisions while ensuring project delivery aligns with business goals.

The AI Automation Intern supports internal teams by improving and automating processes, integrating data, and providing training on IA tools. Requires technical and soft skills such as programming, SQL, communication, and collaboration.

The Applied AI Engineer will support customer adoption of AI products, integrate AI models into applications, and improve product capabilities based on feedback.

The Senior Generative AI Engineer will design, develop, and deploy GenAI models, mentor junior engineers, and ensure the reliability of outputs.

Lead and develop the AI/ML Engineering team for Terabase's software product. Oversee AI/ML initiatives, collaboration across teams, and ensure product quality.

Lead the Docugami Europe AI research lab, manage a team of researchers, propose solutions to scientific problems, and collaborate with academic institutions.

As a Data Science Graduate Student Intern, you will research solutions to scientific problems, collaborate with academia, and deploy findings in production with engineers.

The Applied AI Engineer will onboard customers, deploy AI applications, and collaborate with teams to resolve technical challenges and drive technological transformation.

Develop and maintain web interfaces using React and TypeScript, integrate backend services in Python, collaborate with teams for user experiences, and contribute to architectural discussions.

The role focuses on improving AI cluster resiliency through AIOps solutions, automation workflows, and customer engagement for installations and troubleshooting.

The role involves engaging AI startups, developing solutions, partnering with internal teams, and representing NVIDIA at events to drive market growth.

As a Solutions Architect, you will drive innovation for NVIDIA customers by providing expertise in Generative AI post-training, especially utilizing LLMs and data processing techniques. Responsibilities include building proof-of-concepts, collaborating with various teams to integrate NVIDIA technology, and guiding customers on tools and methodologies for model alignment and training.

As a Senior MLOps, you'll build and maintain data pipelines, design data storage solutions, and deploy model-serving systems, collaborating with ML Engineers for performance and quality.

Lead architecture and execution for data platforms and LLM products, focusing on scalable solutions and team collaboration to drive outcomes.

Lead AI-driven drug discovery initiatives, develop advanced AI models, mentor teams, and bridge AI research with practical applications in molecular modeling and drug design.