Top Artificial Intelligence Jobs in France

Develop and optimize large neural-network tabular models in Python. Profile training and inference pipelines, improve memory efficiency, latency, and throughput. Implement performance-critical components in Rust (and optionally C++), ensure numerical stability and reproducibility, collaborate with researchers to productionize capabilities, and maintain tests and documentation.

The Chief Data & AI Officer will strategize and implement data and AI initiatives to drive business growth and operational efficiency across Pluxee globally. Responsibilities include fostering a data-driven culture, leading data governance, ensuring compliance, and promoting the adoption of AI and advanced analytics.

Ship real open-source integrations and MCP servers to bring SearchApi to agent and automation frameworks. Create PRs, example apps, docs, and integration guides. Stay current with the agent ecosystem, pick high-leverage targets, and work independently to deliver production-ready integrations.

As a Software Engineer at Polar Analytics, you will build core systems, manage data pipelines, and innovate solutions for eCommerce brands while engaging with users to improve reliability and performance.

Lead AI and machine learning architecture, mentor teams, drive innovation, and evaluate tools for AI systems development across global teams.

Design and develop ML/DL models to integrate multi‑omics data for target identification, pathway analysis, and patient stratification. Apply transformers, representation and self‑supervised learning in HPC/cloud environments. Ensure model robustness, interpretability and reproducibility while collaborating with biologists and drug discovery teams to translate biological questions into AI solutions.

Lead enterprise deployments and enablement for Dust customers: define goals, design persona-specific training, build scalable enablement programs and content, monitor adoption, remove blockers, partner with Sales/Product, and establish repeatable best practices for AI adoption and scaling.

Design, implement, and deploy AI solutions using LLMs, RAG, and AI agents. Identify AI use cases, evaluate risks and limitations, support digital and data strategy, and collaborate with teams to deliver production-ready solutions.

As an AI Engineer, you will build AI agents for preventive health, focusing on reasoning, clinical workflows, and ensuring reliable production systems.

The Applied AI Engineer will develop automated MLOps pipelines for integrating and deploying AI models in healthcare robotics, ensuring compliance with regulations and achieving clinical accuracy targets.

Design, scope and govern modular, secure Power Platform and Copilot solutions. Lead architecture workshops, audit environments, produce HLD/LLD, supervise implementations, manage technical teams, and define AI/Copilot standards and best practices.

Design and build business solutions and AI agents on Microsoft Power Platform and Copilot Studio. Lead workshops, audit environments, model automations, run UAT, and produce engineering and integration documentation.

Design and develop scalable .NET software architectures, integrate generative AI/ML services (Azure AI, OpenAI, ML.NET), lead technical workshops, mentor developers, enforce CI/CD/DevOps practices, conduct code reviews, and ensure software quality and security.

Design, build and industrialize Azure-based data platforms: ingest and process batch/real-time data, develop Data Lake/Warehouse/Lakehouse, implement ETL/ELT and DataOps, ensure data quality/security, collaborate with BI (Power BI), support pre-sales and produce technical documentation.

Lead and deliver change workstreams on complex transformation programmes, build multi-stakeholder adoption strategies, measure impact with KPIs and analytics, disseminate an augmented consultant model and AI agents, develop offerings and adoption kits, manage and upskill consultants, and support executive governance and client relationships.

Lead and deliver AI and data transformation engagements from strategy to implementation. Design automation and Infrastructure-as-Code solutions, mentor teams, manage change, and present to clients. Work in multidisciplinary teams on generative AI, intelligent platforms, and large-scale digital transformations.

Lead design and development of scalable .NET architectures integrating generative AI. Provide technical leadership, mentor teams, run workshops, enforce DevOps/CI/CD, code reviews, and ensure performance, quality and security across cloud-based projects (primarily Azure).

Design robust, scalable cloud architectures (AWS) and implement Azure data platform solutions (Data Factory, Synapse, Fabric). Manage databases, data storage/processing, data security, IoT and AI data management. Collaborate with multidisciplinary teams on Generative AI and intelligent platform projects, communicating effectively with clients.

Lead change management workstreams combining frameworks, employee experience design, and AI agents; conduct impact studies, design adoption strategies, run workshops, deploy governance and reporting, support pre-sales, mentor consultants, and contribute to R&D of change products and AI modules.

Lead design and development of scalable .NET architectures integrating generative AI (OpenAI, Azure AI, ML.NET). Provide technical leadership, mentor teams, enforce DevOps/CI-CD and code quality, and drive cloud-native deployments on Azure and Kubernetes.

Design and implement business solutions and agents in the Microsoft ecosystem using Power Platform and Copilot Studio. Facilitate specification workshops, audit systems, assess requirements, perform technical and functional UAT, maintain technology watch, and draft engineering, integration, and UAT documentation.

Design, build, and deploy production LLM- and agent-based systems that automate medical coding in hospitals. Own end-to-end AI features from research and prototyping to deployment and monitoring. Build secure health-data ingestion pipelines, integrate AI outputs into clinical applications, and define the AI roadmap with the CTO.

The role involves performing data-related tasks supporting AI content improvement in French, including data collection, evaluation, annotation, and object tagging.

Lead and build Axelera's AI Infrastructure Systems division to deliver datacenter-class hardware from accelerator cards and OAM/UBB modules to 1U/2U racks. Own architecture, schematics, PCB/layout review, power/thermal/mechanical design, BMC/firmware, bring-up, validation, qualification, NPI, and ramp with CMs/ODMs. Align roadmaps with silicon, SDK, and product teams, engage customers and partners, set engineering processes, manage budget and vendor relationships, and mitigate technical risks through hands-on leadership.

Lead design, training, and evaluation of LLMs for translation and language-quality tasks; build robust evaluation frameworks; architect agentic multi-model workflows; own model development from data curation to production; run reproducible experiments; collaborate with product and engineering and mentor researchers.