TL;DR

Senior Machine Learning Engineer (AI): Designing, building, evaluating, and optimizing AI models and intelligent systems for Ubisoft's information lifecycle with an accent on advanced hybrid search, RAG pipelines, and agentic reasoning. Focus on transforming cutting-edge AI capabilities into robust, scalable, real-world solutions and pushing the boundaries of human-AI collaboration.

Location: Office-based in Paris, France (Saint Mandé)

Company

Ubisoft is a global leader in gaming, creating original and memorable experiences like Assassin’s Creed, Rainbow Six, and Just Dance.

What you will do

  • Design, fine-tune, and optimize machine learning models, including LLM-based, retrieval, and multimodal systems for production use.
  • Develop and improve RAG pipelines and agent-based workflows, including embeddings, vector search, orchestration, and evaluation.
  • Extract insights from internal AI platform data, performing topic extraction, clustering, and trend analysis to transform usage patterns into actionable product insights.
  • Deploy, monitor, and optimize ML models in cloud-native environments, ensuring scalability, reliability, and cost-efficiency.
  • Define evaluation frameworks, run experiments, and continuously improve model quality, robustness, and user impact.
  • Collaborate with software engineers, SREs, and product teams to integrate AI systems into scalable architectures and deliver high-impact solutions.

Requirements

  • Experience: Solid experience in machine learning engineering or applied AI, with proven experience delivering ML systems in production.
  • Programming & Frameworks: Strong proficiency in Python and hands-on experience with ML frameworks such as PyTorch, TensorFlow, JAX, or equivalent.
  • LLMs & Modern AI: Practical experience with Large Language Models, embeddings, transformer architectures, and fine-tuning or prompt engineering techniques.
  • RAG & Retrieval: Experience designing or implementing RAG pipelines, including vector databases, hybrid search, and query optimization strategies.
  • Model Deployment & Cloud: Experience deploying models via APIs using Docker and cloud platforms such as AWS, GCP, or Azure.
  • Data & System Thinking: Solid understanding of data pipelines, experimentation, evaluation metrics, and ML systems operating within distributed, scalable architectures.

Nice to have

  • Experience building or integrating AI agents and multi-agent systems (e.g., LangGraph, CrewAI, Strands Agents).
  • Familiarity with inference optimization techniques such as quantization, distillation, batching, or caching.
  • Experience working with multimodal models (text, vision, audio).
  • Knowledge of MLOps best practices, including model registries, CI/CD for ML, monitoring, and drift detection.
  • Experience operating AI workloads in cloud-native environments (e.g., Kubernetes, serverless) and/or contributing to open-source or research initiatives.

Culture & Benefits

  • Benefit from profit sharing and a yearly company saving plan.
  • Enjoy 25 paid time off days plus 12 additional paid days off.
  • Receive lunch vouchers (9€/day) and 50% of your transportation pass paid by the company.
  • Access healthcare coverage for you and your family, along with many other Ubisoft perks.
  • Take advantage of a gym available in the office building.
  • Benefit from extensive maternity (20 weeks) and paternity/co-parental (7 weeks) leaves.

Hiring process

  • [30 minutes] Phone call with a Recruiter.
  • [60 minutes] Video interview with the manager of the role and the Recruiter.
  • [60 minutes] Final video interview with the Production Intelligence Data Associate Director.