Top Artificial Intelligence Jobs in Lyon

Analyze HR processes for AI opportunities, enhance data quality, configure HR AI solutions, collaborate across teams, and support AI governance.

As a Smart Home Solution Engineer Intern, you will evaluate new smart home technologies, gather information, analyze installations, and propose new product developments.

The Product Manager for AI Customer Support at Alan defines product strategy, collaborates with teams, and enhances AI-driven customer support experiences.

As an AI Product Manager, you will lead the development of AI-enabled Clinical Data products, focusing on multi-modal clinical and genomic data.

As an AI Product Manager, you will lead the application of AI in Health Information Systems, manage product portfolios, and ensure compliance with healthcare standards while delivering technology solutions that enhance patient care.

The AI Programme Manager will oversee AI initiatives across health systems, coordinating delivery, managing stakeholders, and ensuring alignment with strategic goals, while mitigating risks and driving timely execution.

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.

As the Technical AI Lead, you will oversee a global team, ensuring quality in AI products, defining best practices, and collaborating with product teams to deliver AI-driven solutions in healthcare.

Develop and refine NLP projects by improving LLM models, implementing production models, and conducting performance experiments.

Lead product development in the industrial sector focusing on IoT, edge computing, and AI applications. Oversee product lifecycle, conduct market research, and collaborate with cross-functional teams.

As a Senior AI Engineer, you will develop AI-powered features, integrating LLM APIs to enhance user workflows while collaborating with teams to ensure reliability and scalability.

The role involves automating tasks using Github Copilot, managing data for reporting models, and improving documentation practices in a CI/CD DevOps environment.

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.

As a Senior Site Reliability Engineer, you will enhance the reliability and performance of our inference platform, leveraging Kubernetes and Terraform while ensuring smooth scalability of systems under load.

The role involves testing and debugging AI clusters, maintaining hardware, and collaborating with development teams to resolve issues across networking components.

Adapt scripts for dubbing, generate audio using AI tools, refine translations, evaluate voice quality, and handle client feedback while managing multiple productions.

As a Golang Engineer, you will design, develop, and optimize distributed backend systems, focusing on performance, scalability, and P2P communication. You'll collaborate in an Agile environment and improve backend infrastructure while mentoring fellow engineers.

Lead the AIVM product development, overseeing architecture, strategy, and execution while collaborating across teams for successful platform launch.

The role involves training large language models to write production-grade code, comparing snippets, refactoring code, and providing feedback for reinforcement learning processes.

Train large language models to write code by reviewing code snippets and providing feedback for improvements. Requires 3+ years of Ruby experience.

Train and evaluate AI models for computer vision tasks, assess model accuracy, create training data annotations, and suggest improvements for visual data interpretation.

As a Software Engineer in AI, you will train large language models, rank and review code snippets, and provide feedback for improvements.

The role involves training large language models to write production-grade code using Java, performing code reviews, refactoring, and providing detailed explanations for coding decisions.

Train large language models to write production-grade code across languages, review and improve AI-generated code, and maintain the RLHF feedback pipeline.

Design and build simulation environments for robotics research, implement RL algorithms, and evaluate policies for stability and transfer potential. Collaborate with teams and document results.