Top Artificial Intelligence Jobs in Paris

Own the vision, roadmap, architecture, and hands-on delivery of IFS’s Internal Developer Platform. Build developer portals, service catalogs, self-service scaffolding, golden paths, CI/CD integrations, authentication, authorization, and observability workflows. Drive adoption through metrics, feedback, and developer research while partnering with infrastructure, IAM, SRE, and distributed product teams. The role requires production Kubernetes operations, enterprise-scale platform ownership, production AI application experience, and strong technical leadership without direct management responsibility.

Own end-to-end product design for MEDvidi’s AI Track, creating human-AI interaction patterns for clinical tools such as AI Scribe, Chart Review, and AI Receptionist. Gather requirements independently, research provider needs, prototype directly in code using Claude Code or Cursor, collaborate with product and engineering, contribute reusable Storybook components and design-system documentation, validate designs, and guide solutions through release.

Serve as the senior technical expert for EMEA AI organizations training and post-training large-scale foundation models. Advise customers on distributed training infrastructure, PyTorch, Megatron-LM, NeMo, reinforcement learning, GPU utilization, communication overlap, and memory management. Build strategic technical relationships, translate customer needs into NVIDIA product roadmap input, collaborate with research and product teams, and support hackathons, demonstrations, and technical conferences.

Build and deploy reliable, measurable, and safe AI agents for real business workflows. Work within Marketing Engineering and growth pods to identify problems, develop end-to-end solutions, evaluate LLM performance, and measure business impact. The role involves productionizing agent systems beyond demos, using Python, SQL, LLM APIs, and orchestration tools, with potential integration into go-to-market data and marketing systems.

Leads end-to-end architecture for enterprise data, analytics, and AI solutions in a Microsoft-first environment. Translates business requirements into secure, scalable designs and guides prototyping, implementation, architecture reviews, troubleshooting, governance, and production readiness. Requires deep hands-on experience with Azure data platforms, Power BI, enterprise security, Azure OpenAI, and retrieval-augmented generation patterns.

Manage influencer campaigns end to end across multiple brands and markets. Responsibilities include creator casting, briefing, negotiation, contracting, campaign timelines, budgets, approvals, client communications, performance tracking, reporting, and optimization. The role requires using CPV and campaign KPIs to manage commercial outcomes, ensuring content meets brand and compliance requirements, and operating as a power user of Kyra’s platform and AI tools.

Leads DentalMonitoring’s global communications strategy, brand consistency, digital platforms, marketing campaigns, sales collateral, training and education programs, public relations, public affairs, KOL initiatives, and internal communications. Manages communication and marketing professionals while partnering with regional marketing, product, and sales teams to coordinate launches and campaigns worldwide.

Own and grow the Data Layer: build and operate ingestion, transformation, reconciliation, and serving pipelines (raw→refined→curated). Use agentic AI tools to accelerate delivery, ensure data correctness, and partner with backend, AI, and product teams to define reliable data contracts.

Fine-tune and post-train open-weight LLMs using methods such as SFT, LoRA, QLoRA, DPO, and GRPO. Build training data and evaluations, diagnose model failures, improve personalization and multilingual behavior, accelerate reproducible training workflows, and deploy models to production. The role involves using real user behavior to guide iterations across a large-scale AI companionship platform, with collaboration across AI, product, web, DevOps, and leadership teams.

Supports Finance Technology initiatives involving AI use cases, AI solution development, data integration, process automation, reporting, analytics, and enterprise system transformation. The apprentice assists with proofs of concept, data flow monitoring, testing, documentation, deployment, and data quality improvements while collaborating with Finance, Technology, Data, and Business teams.

Lead the architecture and implementation of AI-native product engineering systems, including agent-ready code standards, context infrastructure, self-healing incident workflows, multi-step agentic features, and AI code-review optimization. Ship end-to-end product features, set technical direction, evaluate LLM reliability and trade-offs, and accelerate validated learning through close collaboration with engineering, product, and design teams.

Lead the architecture and implementation of AI-native product engineering systems, including agent-ready code standards, context infrastructure, self-healing incident workflows, multi-step agentic features, and AI code-review optimization. Ship production software, establish technical direction, and partner with product and design teams to accelerate validated learning. The role requires strong backend and distributed-systems expertise, hands-on LLM product experience, and practical use of AI coding tools.

Contribute to AI-powered forecasting and optimization tools for revenue management. Analyze optimization algorithms, monitor decision data, develop performance KPIs, validate new features, write product tickets, and collaborate with Data Science, Machine Learning, Software, and Product teams. Share findings in product discussions and help deliver improvements used by transport and events clients.

Build reliable multi-agent AI systems for real-estate workflows. Responsibilities include developing Python delivery pipelines, context assembly, tool orchestration, verification, report generation, data extraction, evaluation harnesses, observability, regression datasets, and production-quality reliability. The intern will collaborate with architects, clients, and domain experts while working with regulatory, financial, market, and geospatial data.

Conduct research on discrete diffusion models for compliant architectural floorplan generation. Design and evaluate falsifiable ablation studies, improve model architecture, loss functions, conditioning, sampling, and distributed multi-GPU training. Build computer vision pipelines to transform plans, PDFs, and scans into structured training data. Collaborate with AI engineers, researchers, and architects to turn foundational research into deployable design tools.

Join Welo Data’s Swahili contributor network for potential remote AI projects involving text, image, or audio annotation; search, advertising, or chatbot evaluation; prompt creation; and cultural and linguistic accuracy review. Applicants must be native or near-native Swahili speakers based in Kenya, Tanzania, or the Democratic Republic of Congo, with English proficiency, digital-tool comfort, and strong attention to detail. Projects vary in duration and compensation, with details provided before participation.

Develop AI-driven products through hands-on software development and product engineering. Build minimum viable products, solve problems creatively, and help shape future AI applications. The role is available remotely or in Boston and Chicago, with contract options ranging from two weeks to three months or full-time, plus potential revenue sharing.

Six-month AI and Data internship in AlixPartners’ Performance & Technology team. Responsibilities include identifying AI opportunities, prototyping Generative AI use cases, integrating LLMs, engineering prompts and agents, processing data with cloud technologies, developing Python-based data science solutions, and creating business dashboards. The role involves client-facing consulting, collaboration with technical and non-technical stakeholders, frequent travel in France, and work across office and remote environments.

Manage key digital-native accounts in France, driving enterprise AI opportunities from pipeline generation through deployment and revenue realization. Develop account strategies, lead complex deal cycles, forecast consumption revenue, engage C-level stakeholders, and collaborate with solutions, engineering, marketing, finance, and product teams. Analyze market and account data, support customer events, contribute to product strategy, and help recruit and onboard teammates.

Own and improve cashback offer operations across merchant setup, affiliate tracking, coupons, card-linked integrations, gift cards, and merchant performance. Analyze operational data, build health dashboards, investigate failures, design scalable processes, automate repetitive work with AI and Retool, manage outsourced resources, and collaborate with Product, Engineering, and commercial teams to resolve issues and improve reliability.

Designs and maintains scalable cloud data pipelines, data models, ETL processes, machine learning workflows, and AI-ready datasets. The role focuses on data quality, governance, observability, monitoring, CI/CD, containerized deployments, and technical standards. It collaborates with business and technical stakeholders to translate requirements into solutions while applying generative AI technologies and supporting Sanofi’s commercial digital transformation.

Own the Vault product roadmap and lifecycle for a sports media asset platform. Lead discovery with customers, define solutions for content ingest, storage, integrations, AI enrichment, metadata, search, rights, and asset monetization. Partner closely with engineering, sales, and customer success, attend customer events, and prioritize product bets that help sports organizations maximize the value of extensive media archives.

Deploys and operationalizes AI platforms within enterprise client environments. Responsibilities include designing AI architectures, building production agentic solutions, integrating identity, data, security, governance, and workflows, and owning reliability, adoption, scalability, and business value. The role involves rapid prototyping, production deployment, client workshops, executive stakeholder engagement, reusable accelerator development, and enabling client teams to operate solutions independently.

Build and maintain software for clinical AI medical devices across radiology modalities. Develop features, integrate systems, validate and route requests, assemble results, and support production services. Write and review code, create automated and manual tests, and own features through deployment. Ensure quality, regulatory, cybersecurity, documentation, and risk-analysis compliance while collaborating with product, service, and delivery teams.

Leads the enterprise data governance strategy, framework, roadmap, policies, standards, and data quality programs. Establishes metadata, lineage, master data, classification, access, and privacy practices while partnering with IT and Security to support secure AI initiatives. The role resolves cross-functional data issues, aligns governance with regulatory requirements, measures data quality, and develops the governance team in a regulated healthcare or technology environment.