Top Artificial Intelligence Jobs in Lyon

Lead storytelling and communications for Pfizer's AI-native engineering transformation: set strategy, create content and live events, manage budgets and agency relationships, build cross‑functional engagement, track success metrics, and lead a storytelling team to translate engineering work for executives and broader audiences.

Lead design and delivery of AI-powered visualization and investigation features using LLMs. Build reliable, explainable systems combining deterministic product capabilities with generative models, drive prompt/context engineering, evaluation frameworks, and cross-team product-focused technical leadership and mentorship.

Build end-to-end full-stack AI features on a Ruby on Rails backend and React frontend, design and run experiments (A/B tests and AI evaluations), implement AI infrastructure for reliable LLM inference, and iterate quickly to scale production-ready LLM-powered products.

Rotational graduate program within Alan's Insurance team covering enterprise offers, insurance product lifecycle, analytics and repricing, and reinsurance/risk. After a two-month onboarding you'll work cross-functionally with Engineering, Data, Finance and Marketing to build prevention-focused insurance products, leveraging SQL and AI, with coaching and visible impact from day one.

Work with traders, asset operators, and developers to analyze electricity market outcomes, improve trading and operational strategies, and drive customer success. Translate market workflows into product requirements, collaborate with engineering to enhance analytics, dashboards, and optimization models, and lead customer onboarding, implementation, and ongoing technical account management.

Drive development and deployment of AI solutions, translating business needs into product requirements, managing backlogs, and coordinating cross-functional teams.

Own partnership sourcing, negotiation, and deal execution to drive adoption of Walrus across AI and Web3 ecosystems. Build relationships with AI builders, data vendors, compute networks, and web3 partners; lead contract negotiations; and manage cross-functional integration from signing through execution.

Build, operate and scale AI GPU/HPC infrastructure with monitoring, incident diagnosis and remediation. Implement observability, manage lifecycle across regions, participate in on-call rotation, collaborate with product teams, document tools and apply reliability, scalability, and security best practices.

Act as primary technical contact in pre-sales for large-scale GPU and AI projects: analyze AI workloads, design and provision custom GPU clusters, run POCs, translate constraints into business value, and collaborate with sales and engineering to close enterprise deals.

As a Sr. Applied AI Engineer at Zapier, you will build and enhance AI platform capabilities, focusing on LLM Ops and ML Ops to support scalable AI development across teams.

Design, implement, and maintain scalable cloud data pipelines, ETL/ELT and data warehouse solutions. Enable ML workflows and data models, ensure data quality and observability, collaborate with cross-functional teams, and apply CI/CD, containerized deployments, and infrastructure-as-code practices.

The AI Lead Product Manager will define and own the product strategy for AI-powered health data, lead product teams, engage with stakeholders, and ensure compliance with regulations.

Build and operate a composable, event-driven internal platform: design and ship backend services (Python/Go), frontend admin tools (TypeScript/React), integrations with SaaS and cloud APIs, BPMN/workflow orchestration, and LLM/AI tooling across the development lifecycle while owning production reliability, security, and observability.

Build and operate internal, event-driven platform services end-to-end: backend services (Python/Go) on GCP Cloud Run, TypeScript/React UIs, integrations with third-party SaaS (REST, webhooks, OAuth), BPMN workflow orchestration, and apply AI tooling across the development lifecycle while ensuring security, observability, and production reliability.

Build and operate internal, event-driven platform services and UIs across the stack. Integrate third-party SaaS via APIs/webhooks/OAuth, implement observable BPMN workflow orchestration, use AI tooling throughout the SDLC, review AI-generated code, and ensure production reliability, security, and cost control.

Build and operate internal, event-driven platform services and UI features end-to-end. Integrate third-party SaaS and cloud APIs, implement observable BPMN workflow orchestration, use AI tooling across the SDLC, ensure security and reliability in production, and contribute engineering standards and playbooks.

The Backend Engineer will develop AI Agents, design scalable systems, integrate ML services, optimize performance, and mentor junior engineers.

Design, develop, and maintain production ML services and AI agents; extend agent capabilities and hybrid human-expert workflows; implement observability for agent quality and system reliability; collaborate across ML and engineering to deploy and operate LLM-based features in production.

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.

The AI-First Full-Stack Engineer will lead full-stack development using Node.js and Next.js, integrating AI workflows and orchestrating Claude agent teams for efficient engineering processes, ensuring compliance with healthcare standards.

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 end-to-end product development for an agentic AI platform for drug discovery: prototype LLM/agentic workflows, convert manual scientific workflows into reusable products, evaluate integrations, collaborate with scientists, engineers and customers, and support demos, pre-sales and adoption.

Lead development of proactive AI-driven sales workflows and roadmap for Account Executives. Work hands-on with prompts, connectors and evaluation, align with sales and AI platform teams, prioritize high-impact automations, and drive outcomes like reduced low-value work, faster offer creation, and higher win rates.

Own end-to-end product for a slice of Nebius AI compute platform: define strategy, APIs, and roadmaps; drive cross-team delivery; conduct structured discovery; measure adoption and platform outcomes; engage engineering as a technical peer; and close operational feedback loops to improve reliability and customer experience.

Lead the product design team to create innovative user experiences for an AI-based platform, conducting research and defining design vision.