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IT Developer

2 months ago

Montreal, Quebec, Canada Ubisoft Full time
Job Overview

Ubisoft is seeking a highly skilled IT Developer to join the Consumer Data Domain team within the Ubisoft Data Office (UDO) department. This team's primary objective is to leverage data to enhance the consumer experience by engaging with users throughout their journey.

As an IT Developer in this role, you will be responsible for designing and developing scalable machine-learning systems to ensure the trust and safety of our users. You will also be responsible for deploying production-grade products by combining research and engineering cycles from the prototype phase to delivery.

Key Responsibilities
  • Design and Development: Design, prototype, build, and maintain microservices & APIs that deliver data and models to teams and projects across Ubisoft.
  • Data Pipelines and Processes: Build pipelines and batch processes that move and transform data.
  • Cloud Infrastructure: Build and manage a scalable infrastructure in the cloud.
  • Platform Improvement: Participate in decisions and implementations to improve the platform's quality.
  • Proof-of-Concept Projects: Participate in proof-of-concept (POC) projects to advance your understanding of new data and Machine Learning related technologies.
  • Code Optimization: Write, optimize, and produce high-quality code that can run at scale, using modern best practices such as Machine Learning Operations (MLOps).
  • Collaboration: Collaborate with data and machine learning engineers to ship models or prediction pipelines to production in our internal or public cloud infrastructures.
  • Project Ownership: Take ownership of the projects you build while ensuring they progress accordingly.
Requirements
  • Experience: Previous experience in Software/Data engineering, or a related field.
  • Programming Skills: Solid experience with programming languages such as Python, Rust, or Spark.
  • API Experience: Experience building and interacting with REST APIs and familiarity with the principles of microservice architecture and API design.
  • Cloud Technologies: Proficient experience using Kubernetes.
  • Cloud Platforms: Good experience using cloud technologies such as AWS and Azure.
  • Machine Learning Deployment: Experience deploying machine learning models to production.