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Machine Learning Developer
Ubisoft
Job Summary
Location
Montreal ,QC
Job Type
Contract
Visa
Any Valid Visa
Salary
PayRate
Qualification
BCA
Experience
2Years - 10Years
Posted
11 Nov 2024
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Job Description
Job Description Ubisoft IT is looking for a Machine Learning Developer to join the Consumer Data Domain team which is part of the Ubisoft Data Office (UDO) department. This team’s main mission is to leverage data to improve the consumer experience by engaging with all our users along their journey.
As a Machine Learning Developer joining this team, you will be responsible for building scalable machine-learning systems to preserve 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.
Responsibilities:
Design, prototype, build, and maintain microservices & APIs that deliver data and models to teams and projects across Ubisoft;
Build pipelines and batch processes that move and transform data;
Build and manage a scalable infrastructure in the cloud;
Participate in the decisions and implementations to improve the platform’s quality;
Participate in proof-of-concept (POC) projects to advance your understanding of new data and Machine Learning related technologies;
Write, optimize, and produce high-quality code that can run at scale, using modern best practices such as Machine Learning Operations (MLOps);
Collaborate with data and machine learning engineers to ship models or prediction pipelines to production in our internal or public cloud infrastructures;
Take ownership of the projects you build while ensuring they progress accordingly.
Qualifications Previous experience in Software/Data engineering, or a related field;
Solid experience with programming languages such as Python, Rust, or Spark;
Experience building and interacting with REST APIs and familiarity with the principles of microservice architecture and API design;
Proficient experience using Kubernetes;
Good experience using cloud technologies such as AWS and Azure;
Experience deploying machine learning models to production.
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