Top Artificial Intelligence Jobs in Paris

Research and engineer large multimodal and reinforcement-learning models for robotic agents: design, train, evaluate models; prototype in simulation and on hardware; build data pipelines, simulation environments, and distributed training infrastructure; collaborate to scale promising approaches into production and publish results.

Design and build research prototypes and production-capable systems to enable portable, interoperable agent and model workflows. Develop model routing, provider abstractions, memory and context representations, benchmarking suites, and evaluation protocols. Run ML experiments, implement robust APIs and integration layers, collaborate across research and engineering, and communicate results via reports, demos, publications, and open-source releases.

Onboard and support client projects onto Nebius' Azure AI platform using runbooks and golden paths. Adapt Terraform modules and CI/CD pipelines, support ML workload deployment and lifecycle management, capture delivery gaps, and provide structured feedback to Platform Engineering while maintaining security and governance.

Advise AI-focused customers to design scalable AI solutions and manage large-scale GPU deployments. Deliver technical presentations, documentation, and webinars. Collaborate with engineering and product teams to prioritize and convey customer feedback.

As an AI Engineer, you'll design AI tools for authors, enhance internal workflows, and build tools for AI development, collaborating with teams to identify AI opportunities.

Build and test AI-agent features and internal agent frameworks for a proactive cybersecurity platform. Implement and integrate generative AI systems (agents and RAG), stay current with AI research, and apply innovations to product development and evaluation within a security-focused environment.

Design, build, evaluate, and deploy LLM-driven features and AI systems. Collaborate with engineering and product teams to implement RAG, monitoring, CI/CD, and scalable cloud ML deployments while continuously improving model performance.

As a Senior Software Engineer at Razer, you will develop high-performance C++ systems for real-time game data acquisition, event tracking, and video generation, while optimizing engine performance and ensuring system reliability.

Lead Oyster's data platform and AI strategy, centralize AI initiatives into production systems, build scalable data and MLOps infrastructure, modernize knowledge architecture and semantic search, partner cross-functionally to embed AI into products and workflows, enforce tooling standards and governance, and drive organizational adoption and change management for AI-assisted operations.

Lead deployment, debugging, benchmarking, and performance optimization of large-scale GPU training and inference workloads. Work with NVIDIA teams and external customers to diagnose cluster bottlenecks, improve efficiency, guide scaling strategies, and contribute to resiliency for Europe's Sovereign AI initiatives.

The role involves reviewing and evaluating AI-generated outputs, correcting text and analyzing content with a keen focus on cultural relevance and accuracy.

The Senior AI Product Manager will own the Data & AI roadmap, defining strategy and leading product initiatives from discovery to deployment while optimizing processes and documentation.

The Backend Engineer will develop and maintain features for Restream web services, design backend APIs, ensure infrastructure resilience, and contribute to a collaborative team environment.

Review, evaluate, and annotate AI-generated text, images, audio, and video for quality, consistency, and guideline compliance. Perform quality checks, identify edge cases, participate in calibration activities, and provide feedback to improve datasets and annotation workflows for multilingual AI projects.

Design and implement CI/CD and IaC for LLMs, automate model and dataset versioning, provision GPU/TPU infrastructure, enable safe experiment gates and progressive delivery, and build monitoring/observability and feedback loops for production LLM endpoints.

Produce high-performing AI-driven paid ads from concept to final cut using AI avatars, voiceovers, b-roll, and motion graphics. Match and iterate on existing ad styles, collaborate with copywriters, optimize for hooks/pacing/CTAs, scale volume, and stay current with AI tools to innovate creative formats.

Define product vision and strategy via market research and data analysis; build prioritized roadmaps; collaborate with PMs, designers, and engineers to launch products; communicate with stakeholders; track performance and iterate post-launch.

The Fullstack Applied AI Engineer will build and maintain the infrastructure for Lumo's AI platform, integrating privacy-preserving technologies and ensuring high availability for millions of users.