Senior Machine Learning Engineer - ai Initiatives W - M - Nb H/F - 75

Ubisoft is a global leader in gaming with teams across the world creating original and memorable gaming experiences, from Assassin's Creed, Rainbow Six to Just Dance and more. We believe diverse perspectives help both players and teams thrive. Ifyou'repassionate about innovation and pushing entertainment boundaries, join our journey and help us create the unknown!Join the Ubisoft AI Initiatives team and architect the future of the information lifecycle at Ubisoft. From advanced hybrid search and RAG pipelines to complex, agentic reasoning, we are engineering the tools that turn raw information into high-velocity decision-making. If you want to push the boundaries of how humans and AI collaborate to solve complex problems, this is your arena.
We are seeking a highly skilled Machine Learning Engineer to design, build, evaluate, and optimize AI models and intelligent systems that power these applications. You will work at the intersection of machine learning research, large-scale data systems, and production engineering - transforming cutting-edge AI capabilities into robust, scalable, real-world solutions.

What you'll do

- Design and Optimize AI Systems: Design, fine-tune, and optimize machine learning models, including LLM-based, retrieval, and multimodal systems for production use.
- Build Intelligent Retrieval & Agentic Pipelines: Develop and improve RAG pipelines and agent-based workflows, including embeddings, vector search, orchestration, and evaluation.
- Extract Insights from Internal AI Usage: Leverage internal AI platform data (chat interactions, prompts, usage logs) to perform topic extraction, clustering, and trend analysis, transforming usage patterns into actionable product insights.
- Productionize and Scale Models: Deploy, monitor, and optimize ML models in cloud-native environments, ensuring scalability, reliability, and cost-efficiency.
- Evaluate and Improve Model Performance: Define evaluation frameworks, run experiments, and continuously improve model quality, robustness, and user impact.
- Collaborate Across Engineering and Product: Partner with software engineers, SREs, and product teams to integrate AI systems into scalable architectures and deliver high-impact solutions.