Top Artificial Intelligence Jobs in Paris

The role involves designing and evolving Ipsen's Data & AI platforms architecture, ensuring optimal use of the platform, and collaborating with project teams. Key responsibilities include defining architectures, promoting best practices, and contributing to the platform roadmap while aligning with stakeholders.

Write and shape Sidetrade's equity story for institutional investors: prepare earnings presentations, press releases, investor decks, analyst Q&A, roadshow materials, and investor communications in English and French. Manage investor CRM, organize meetings and shareholder events, run market and competitive research, and support CEO/CFO preparation for financial communications while using AI tools like Claude.

Design and implement execution primitives for AI/agent workflows in Kestra's Java core, build and maintain plugins to connect LLM providers and agent frameworks, convert agent use cases into reusable blueprints with product, and ensure AI executions are observable, debuggable, correct, and reliable.

Own AI workflows product: discover and validate AI use cases with customers, define roadmap and specs, create reusable blueprints with engineering, and prioritize what not to build.

As an AI-native growth hacker, you will implement a growth strategy, focusing on a specific growth wedge, leveraging AI tools, and measuring performance to scale successfully.

Drive the full AI product lifecycle, building LLM-powered workflows, defining requirements, managing product performance, and collaborating across teams.

Lead development and scaling of AI-powered clinical applications using LLMs. Gather user and industry requirements, write product specifications, prioritize roadmaps, coordinate sprints and releases, validate quality with engineering and QA, and design generative AI capabilities to streamline pharmaceutical workflows and regulatory documentation.

Lead product discovery and delivery for Doctrine's legal AI platform: understand legal users, define metrics and requirements, run experiments/MVPs, validate with users, align cross-functional teams, and continuously improve product adoption and performance.

Nebius seeks a Senior ML Engineer for AI R&D focusing on applied research in reinforcement learning and agent training, requiring deep expertise in machine learning and software engineering.

Partner with Account Executives to present Arize's GenAI observability platform, lead technical demos and discovery, design and run PoCs, advise on GenAI/LLM best practices, handle technical objections, and build relationships with technical and business stakeholders across prospective customers.

Lead end-to-end architecture for enterprise data, analytics, and AI in a Microsoft-first environment. Translate business needs into secure, scalable designs, prototype and guide delivery teams, ensure governance, security, and production readiness, and enable enterprise AI (Azure OpenAI, RAG) and BI (Power BI) solutions.

Build and operate distributed backend services and genomic reasoning engines that combine whole genome bioinformatics with AI. Design scalable data models, retrieval and vector search systems, and deterministic guardrails to ensure scientifically accurate, explainable genomic AI for production use.

Design and build production AI systems and distributed backend services that enable genomic reasoning, retrieval, and data platforms. Integrate genomic annotations and interpretation logic, architect high-performance data models and storage across PostgreSQL, DuckDB, Qdrant, Redis, and Spark. Ensure AI outputs are accurate, explainable, and grounded in genomic evidence while collaborating across engineering and bioinformatics teams.

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.

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.

The Senior AI Engineer will develop AI solutions, fine-tune models, monitor performance, and collaborate with teams to embed AI capabilities, focusing on generative AI and LLMs.

Design and implement backend intelligence for autonomous spatial workflows: architect multi-step agentic execution paths, state tracking and memory systems, consume streaming MCP data, and integrate alerting/notification pipelines (Slack, webhooks) driven by autonomous decisions.

Provide high-volume, empathetic player support via Zendesk; investigate account issues, escalate and document complex cases, identify recurring problems, and drive automation and AI improvements with Product and Engineering to reduce tickets and improve CSAT.

Lead AI, Data and Technology due diligence, value creation and transformation engagements for private equity clients. Assess architectures, AI maturity, technical risks and operating models; define AI/GenAI strategies, prioritize use cases, lead transformation programs, manage senior client relationships, drive business development, and mentor project teams.

Lead Technology & AI due diligence and transformation workstreams for private equity and corporate clients. Assess tech stacks, data foundations, AI maturity, technical debt, scalability and cybersecurity; structure GenAI adoption and use-case prioritization; recommend platforms, governance and operating models; support PMO and change management; present findings to executives and coach junior staff.

Lead strategy and experimentation to maximize the company's presence in AI-driven search. Design measurement frameworks for LLM visibility, run tests to understand LLM citation behavior, integrate data sources, and collaborate with Product, Engineering and PR to optimize site architecture, schemas, and APIs for AI ingestion and perception.

The Business Development Rep will qualify clients and manage outreach in AI Cloud sales, engaging technical audiences and developing partnerships.

The AI Software Engineer will develop and improve Joko's AI shopping assistant, focusing on architecture, evaluation, data management, and personalized user experiences, while collaborating with product teams.

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.