Senior Machine Learning Engineer (W/M/X)

Location: Saint-Mandé, IDF, fr

Company Description

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. If you’re passionate about innovation and pushing entertainment boundaries, join our journey and help us create the unknown! 

Job Description

Ubisoft is natively data-driven: from the core of our games to our marketing actions, we’re leveraging data and algorithms. 

Part of the Ubisoft Data Office, our team operates within the Player Domain, focusing on player safety and security. We build and deploy machine learning systems that keep our players protected — from detecting sanction circumvention using Graph Neural Networks (GNNs) to real-time identification of toxic chat using transformer models. Our scope is broad: NLP, anomaly detection, graph learning, and large language models.

Your role:

Build scalable machine learning systems to preserve the trust and safety of our players. Our motto is to never stop at the prototyping phase — we combine research and engineering cycles with the objective of deploying production-grade products that have a real impact at scale. You will tackle hard problems at the intersection of NLP, anomaly detection, graph learning, and LLMs.

We are looking for a Senior Machine Learning Engineer with proven production experience, someone comfortable moving fluidly between research and engineering.

Missions:

The archetypal missions for this position would be to: 

• 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.

Qualifications

• 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).

Additional Information

Ubisoft's perks
💰 Profit Sharing, yearly company saving plan. 25 paid time off + 12 additional paid days off. 50% of your transportation pass is paid by the company, lunch vouchers (9€/day), healthcare for you and your family, and lots of Ubisoft additional perks. 
👶 Maternity leaves of 20 weeks, paternity/co-parental leaves of 7 weeks. 
📍 Our office is located in Saint Mandé, (Metro line 1, Saint Mandé station). Gym available in the building.

Information about Ubisoft 
Ubisoft offers the same job opportunities to all, without any distinction of gender, ethnicity, religion, sexual orientation, social status, disability, or age. Ubisoft ensures the development of an inclusive work environment which mirrors the diversity of our gamers’ community.