Top Artificial Intelligence Jobs in Lyon

Own the lifecycle of AI products by translating business priorities into executable roadmaps, partnering with engineering and design, driving delivery, and incorporating user feedback. Lead client demonstrations, define and evaluate product metrics, coordinate cross-functional teams, and align product development with broader innovation strategy. The role requires strong product management, leadership, communication, analytical, agile, and user research skills.

Build Solidgate’s ML/AI function from the ground up, developing real-time payment routing models and production pipelines. Own the full ML lifecycle from experimentation and A/B testing through deployment, while solving modeling challenges involving large-scale transactional data. Partner with Product, Engineering, and Data Platform teams to deliver measurable improvements in conversion, approval rates, losses, and revenue.

Leads OKX’s global marketing compliance function, building policies, controls, review and approval processes, monitoring programs, and regulatory change management for advertising, promotions, social media, influencers, affiliates, and product launches across CeFi and DeFi. Partners with Marketing, Product, Legal, Risk, and Compliance teams; manages incidents, supports audits, delivers training, and scales the compliance team and framework.

Lead the engineering function on a remote consulting mission by setting technical direction, managing and mentoring engineers, driving the roadmap, overseeing complex delivery, improving engineering practices, and partnering with product and business stakeholders. The role requires hands-on technical leadership, architectural judgment, agile expertise, and evaluation of emerging technologies including cloud, AI, and blockchain.

Lead the engineering function for a growing technology company on a renewable consulting mission. Responsibilities include setting the engineering roadmap, managing and mentoring engineers, guiding architecture and technical decisions, leading complex projects, improving engineering practices, and collaborating with product and business stakeholders. The role requires hands-on technical involvement, strong software engineering expertise, and the ability to evaluate emerging technologies including cloud, AI, and blockchain. French fluency and strong English communication skills are mandatory.

Leads global FP&A activities, including financial analysis, annual and long-term planning, forecasting, management reporting, investment evaluation, and performance reviews. Drives standardized planning processes, finance digitalization, AI adoption, data-quality improvements, cost-saving initiatives, and profitability improvements. Partners with senior stakeholders and global business lines, communicates financial insights, and supports training and knowledge sharing across Finance.

Own data pipeline workstreams and cloud data warehouse solutions; develop performant data models, ETL/ELT processes, and machine learning workflows. Implement data quality, governance, monitoring, observability, CI/CD, containerized deployments, and infrastructure-as-code practices. Partner with cross-functional teams to translate business needs into technical delivery plans, troubleshoot production issues, and improve engineering standards through documentation, reviews, and knowledge sharing.

Build and own AI models, data pipelines, evaluation suites, and AI product features for construction procurement software. Develop document extraction and workflow automation using generative AI, LLMs, RAG, and optimization algorithms. Design complex data models, integrations, backend services, and production systems using Go, GraphQL, PostgreSQL, and AWS.

Lead design and build of an end-to-end AI contract-review agent: prompt orchestration, RAG pipelines, fine-tuning, web UI and tooling, data/model infra, deployment (CI/CD/cloud), and product-driven features like assumption mapping and contract diagnostics.

Designs end-to-end GPU and networking reference architectures for NVIDIA AI Cloud Partners. Supports customer opportunities, manages technical accounts, delivers demonstrations, proofs of concept, roadmap presentations, training, and technical project management. Troubleshoots networking and system performance issues, supports complex deployments, and provides product feedback to engineering. Requires expertise in data centers, cloud applications, networking protocols, Linux, PCIe, NICs, and hardware architecture, with approximately 20% travel.

Owns a customer territory and drives end-to-end sales of Microsoft AI-powered business process solutions. Responsibilities include territory planning, forecasting, customer discovery, solution selling, stakeholder mapping, partner collaboration, pipeline development, deal execution, adoption planning, and revenue growth. The role requires engaging French- and English-speaking customers, explaining AI-enabled transformation across sales, service, finance, and operations, and coordinating account, technical, services, and partner teams to close opportunities.

The AI Engineer will build data pipelines and improve ML systems for reliability in production. Responsibilities include schema design, data infrastructure, and model evaluation, ensuring high-quality outputs and integration with product workflows.

Lead enterprise AI solution architecture across reusable capabilities, defining engineering patterns, integration designs, deployment strategies, security controls, monitoring, lifecycle management, and technical standards. Partner with application, platform, infrastructure, data, DevOps, security, and delivery teams. Contribute hands-on to proof-of-concepts and production AI solutions while guiding technology adoption and enterprise AI roadmap decisions.

Leads NVIDIA’s global public-sector AI business development strategy across EMEA. Collaborates with sales, marketing, solution architects, developer relations, and partners to drive GPU adoption, pipeline growth, account planning, sales enablement, government agency engagement, and major deal execution. Develops AI use cases, market assessments, sales tools, case studies, and customer relationships while supporting regional go-to-market execution and platform adoption.

Owns full-cycle recruiting for commercial, operational, and technical roles across global markets. Responsibilities include sourcing passive candidates, building pipelines for hard-to-fill positions, advising hiring leaders, coordinating interviews and offers, maintaining accurate Greenhouse data, and improving hiring processes through systems thinking, data, AI, and automation.

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.

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.

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.

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.