Top Artificial Intelligence Jobs in Lyon

Own ElevenCreative’s agency and platform partnerships from 0 to 1. Identify strategic partners, build senior relationships, define commercial models, enable adoption, develop integrations and joint go-to-market programs, and convert partnerships into measurable product usage and revenue. Collaborate with Sales, Product, Marketing, and Engineering while monitoring AI creative trends, customer needs, and competitive dynamics.

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.

Owns commercial success, revenue, and strategic relationships for embedded HR technology partners. Responsibilities include managing a $10M+ annual bookings target, developing partner sales motions, enabling partner sellers, driving pipeline and ARR growth, resolving commercial issues, leading executive business reviews, expanding partnerships, coordinating cross-functional teams, and managing partner account managers and embedded sales leads.

Develops and deploys enterprise AI solutions, especially LLM and VLM applications, TTS, STT, and machine learning models. Responsibilities include model research, training, fine-tuning, evaluation, optimization, API and microservice integration, production deployment, monitoring, MLOps, CI/CD, security, scalability, and cost optimization. The role requires close collaboration with data engineers, DevOps, product teams, project managers, and clients to deliver reliable, production-ready AI systems.

Design, build, optimize, deploy, and monitor production AI/ML solutions, especially LLM and VLM applications. Develop model integrations, APIs, MLOps pipelines, RAG systems, and scalable serving infrastructure. Apply software engineering, testing, CI/CD, observability, security, and compliance practices. Own model lifecycles from data preparation and research through production maintenance. Collaborate with engineers, project managers, clients, and stakeholders while mentoring junior engineers and evaluating emerging AI techniques.

Hands-on technical lead responsible for designing, coding, and delivering enterprise data and AI systems. Leads cross-functional engineering teams, defines architectures, reviews designs and code, mentors engineers, and enables scalable AI development and operations. The role addresses complex enterprise ecosystems, modernization, cybersecurity, data governance, responsible AI, compliance, and regulated environments. It also supports executive stakeholder relationships, proposals, and expansion of data and AI platform capabilities.

Create narrative-driven, long-form cinematic videos using AI-first workflows, from scripting and prompting through generation, editing, compositing, motion graphics, color correction, and final delivery. Maintain character and scene consistency across sequences, experiment with emerging AI video models, refine production workflows, and independently execute creative direction. The role includes stylized and explicit adult content and requires strong storytelling, technical judgment, rapid iteration, and collaboration.

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 Solidgate’s new ML/AI function, developing production machine learning models, recommendation systems, and real-time transaction-routing decision systems. Own experimentation from ideation through A/B testing and deployment, engineer features from high-cardinality transactional data, integrate emerging AI technologies, and collaborate with Product, Engineering, and Data Platform teams on training and analytics pipelines.

Build and iterate AI systems spanning computer vision, image manipulation, video generation, and agentic data analysis. Own the full pipeline from model research and API integration through scalable web application deployment. Develop rapid MVPs using AI-assisted tools, orchestrate multiple models into autonomous workflows, and test solutions in e-commerce operations before scaling them into SaaS products.

Owns planning, activation, optimization, testing, budgeting, and reporting for paid campaigns across TikTok, Meta, and YouTube. Manages $1M+ budgets, presents data-driven recommendations to clients, tracks platform changes, and partners with strategy and creative teams. The role also mentors a Paid Media Executive and establishes team standards for campaign QA, reporting, naming conventions, and optimization practices.

Build and grow Cloudera’s sovereign cloud business across EMEA. Develop provider and customer relationships, create marketplace offerings, lead discovery and value discussions, coordinate cross-functional teams, enable partners, generate pipeline, and drive sales motions. Own regional sovereign cloud pipeline, forecasts, bookings, and revenue. The role requires enterprise cloud, data, AI/ML sales experience, sovereign cloud expertise, complex deal leadership, executive communication, and strong hunting skills.

Lead technical engagement with major AI model builders, integrating NVIDIA GPUs, DGX systems, networking, CUDA-X libraries, NeMo, and TensorRT into large-scale training and inference pipelines. Build strategic technical partnerships, optimize model architectures and infrastructure, influence NVIDIA product roadmaps, communicate with senior engineering and research leaders, and promote scalable generative AI best practices.

Own the AI cost visibility product end-to-end, building Go backend services, APIs, and TypeScript/React interfaces. Translate cloud AI spend and usage data into clear FinOps experiences, while driving architecture, reliability, monitoring, and iteration. Collaborate closely with customers and product stakeholders, use AI throughout the engineering workflow, mentor peers, and shape product direction in an ambiguous market.

Own the AI cost visibility product end to end, developing Go backend services, APIs, data processing, and TypeScript/React interfaces. Translate AI spending data into clear FinOps experiences, work closely with customers and product needs, and use AI throughout the engineering workflow. Lead feature design, implementation, release, monitoring, and iteration while setting engineering standards, mentoring peers, and building scalable cloud-based SaaS capabilities.

Own AI cost visibility features end-to-end, from customer problem discovery and system design through implementation, release, monitoring, and iteration. Build scalable Go backend services, APIs, and TypeScript/React interfaces that process and present cloud AI spend data. Apply AI throughout the engineering workflow, contribute to product direction, understand FinOps and AI economics, mentor peers, and uphold reliable engineering practices.

Build and scale the partner ecosystem for Razer QA Companion-AI across game studios, publishers, and QA providers. Responsibilities include developing partnership strategy, negotiating and onboarding partners, managing executive relationships, driving co-selling and co-marketing initiatives, identifying integrations with Product and Engineering, enabling partners, supporting pipeline growth, monitoring AI and software industry trends, representing the company at events, and measuring partnership performance.

Owns NVIDIA’s EMEA go-to-market motion for its Agentic AI Platform. The role drives customer and partner adoption across enterprise, AI-native, cloud, public sector, defense, and regulated environments. Responsibilities include positioning NVIDIA AI technologies, developing sales enablement and reference architectures, guiding model licensing and security considerations, coordinating cross-functional teams, supporting secure deployments, and translating customer requirements into product and commercial improvements.

Leads NVIDIA’s EMEA go-to-market strategy across agentic AI platforms, open models, enterprise and infrastructure ISVs, cloud providers, marketplaces, and partner ecosystems. The role prioritizes strategic partners and workloads, builds executive relationships, drives partner-led software revenue programs, and mentors regional leaders. Candidates need 15+ years in enterprise software, cloud, AI platforms, alliances, technical sales, or ecosystem leadership, including extensive team management experience.

Build, operate, and improve production services that deliver machine learning models within exocad’s AI Design product. Responsibilities include model serving APIs, containerized deployments, versioning, staged rollouts, rollback automation, infrastructure provisioning with Terraform and AWS, monitoring, observability, and performance tuning. The role also contributes to training and labeling infrastructure and requires collaboration across engineering, product, and global teams, including work across AWS global and China environments.

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 EMEA customers in deploying and optimizing large-scale AI inference on multi-node GPU clusters. Architect dense and Mixture-of-Experts inference pipelines, improve quantization, speculative decoding, prefill/decode disaggregation, KV cache management, and workload scheduling. Collaborate with NVIDIA product teams and engage the developer community through workshops, hackathons, and reference architectures. Advise ML engineers, researchers, and systems architects on high-performance inference across thousands of GPUs.

Serve as a technical bridge between NVIDIA’s generative AI platform and AI-native customers. Guide diffusion model training and deployment, optimize image and video generation pipelines across single- and multi-GPU environments, diagnose vision workload bottlenecks, and provide guidance on model architectures, inference efficiency, video tokenization, and multimodal systems. Translate customer feedback into product improvements and contribute technical demos, workshops, and reference implementations for the EMEA developer community.

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.

Develop and optimize multimodal AI solutions for document intelligence, personalization, and image/video analysis. Build production-ready pipelines, guide customers on model training across modalities, optimize vision encoders and video processing for latency, and translate customer needs into NVIDIA product roadmaps. The role also involves technical relationship management, developer engagement through talks and hackathons, and creating demos and reference architectures.