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# Senior Machine Learning Engineer

- **Company:** Ubisoft Entertainment.
- **Location:** Saint-Mandé, France
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Clean Code Principles, Microsoft Azure, Continuous Integration, Distributed Computing Environment, Python (Programming Language), Machine Learning, Cloud Services, Graph Neural Networks, Retrieval-Augmented Generation, Large Language Models, Prompt Engineering, Apache Spark, Deep Learning, Transformer Architectures, Machine Learning Operations, Drift Detection, Software Version Control, Databricks
- **Published:** October 31, 2026
- **Apply:** https://jobs.smartrecruiters.com/Ubisoft2/744000158700774-senior-machine-learning-engineer-w-m-x-

## About the Role

We are looking for a Senior Machine Learning Engineer with proven production experience, someone comfortable moving fluidly between research and engineering., * Strong Python software engineering skills: clean code, testing, documentation, CI/CD.

 * Proven experience deploying and monitoring production ML models (MLOps, model serving, drift monitoring).
 * Hands-on experience with NLP / LLMs: fine-tuning transformer models, prompt engineering, RAG, or LLM-based pipelines.
 * Experience with graph-based ML (GNNs) is a strong plus.
 * Knowledge of anomaly detection or fraud/trust & safety systems in a production context.
 * Experience with distributed data processing (Spark) and cloud data platforms; familiarity with Databricks (DAB, Delta Live Tables) or Azure-specific services is a plus.
 * Strong communication skills; English is mandatory (presentations, cross-team collaboration, reporting).
 * Ideal candidate: experience with token classification (NER, sequence labelling) and/or hands-on GNN training (node classification, link prediction, graph construction pipelines).

## Description

* Design, train, and deploy ML models across a range of player safety and security use cases, spanning NLP, anomaly detection, and graph-based learning.
 * Evaluate and implement state-of-the-art ML techniques - adapting the latest research in deep learning, NLP, and graph learning to production constraints, implementing from scratch when needed.
 * Take full ownership of the projects you build: interact with stakeholders, define success metrics, monitor live systems, and iterate.
 * Write, optimise, and ship high-quality code that runs at scale, applying modern MLOps best practices (CI/CD, model versioning, observability).
 * In collaboration with data and software engineers, deliver models and prediction pipelines to production on our internal or public cloud infrastructures.