Software Engineer – MLOPS

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

What you bring to the team

• 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

Additional Information

• Your CV highlighting relevant skills and experiences
• Links to projects, code repositories, or systems you have contributed to