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Ubisoft

Montreal (Administrative Region) / Global

Software Engineer – MLOPS

Job Description

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 create the unknown!

Job Description As a Machine Learning Operations Software Engineer at Ubisoft Montréal, you will help build reliable and scalable systems that protect the trust and safety of our players.

You will join the Player Data domain within Ubisoft's Data Office, whose mission is to use data to support players throughout their journey in a safe and respectful environment.

This role combines applied research and software engineering, with a strong focus on production deployment.

What you'll do Lead end to end projects, from design to real world usage

Design, develop, and maintain application services and APIs for data and model sharing

Build and operate large scale data processing pipelines

Deploy and manage scalable cloud infrastructures

Improve platform quality and reliability

Contribute to exploratory projects testing new data and machine learning approaches

Write clean, efficient, and maintainable code designed for scale

Apply modern deployment and monitoring practices for machine learning systems

Collaborate closely with data and machine learning specialists to bring models into production

Qualifications Strong skills in software development or data engineering, using Python or Rust

Experience designing and consuming web service APIs

Practical knowledge of cloud environments and containerized systems (Kubernetes, ArgoCD, AWS, Terraform)

Ability to connect high level vision with technical details

Collaborative mindset with clear and respectful communication

Working knowledge of machine learning, including advanced models

Experience deploying predictive models into production

Familiarity with large scale data processing tools or platform operations, an asset

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