Machine Learning Developer - AI/ML
Montreal, QC, Canada
Ubisoft
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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
The Data Platform Group, part of the Ubisoft Data Office within Ubisoft IT, develops Ubisoft's data platform and manages data services and tools for all of the company's data. As a trusted enterprise-wide resource, our products offer the tools and data infrastructure needed for the development of data services and products by all Ubisoft teams.
The Machine Learning Developer - AI/ML role contributes to the establishment, maintenance, and evolution of the platform and internal tools to enable the development and deployment of machine learning models. The person works closely with online system and operations specialists, programmers and data scientists. The specialist is responsible for the optimization of processes for the production launch of machine learning projects. The person is responsible for ensuring the security, robustness and performance of machine learning solutions during production deployments.
What you'll do
- Govern and contribute to the industrialization of ML/AI projects, focusing on the deployment and maintenance of pipelines and models in production.
- Contribute to the identification of new or improved approaches and technical tools.
- Acting as a consultant to guide technologies and/or advising on proofs of concept for forecasting/prescribing and AI projects.
- Design and implement services, tests, and interfaces that support the deployment of ML projects.
- Ensure the security, robustness, and performance of ML solutions during production deployments.
- Design and implement scalable, continuous, and automated processes for deploying, monitoring, and versioning ML models.
- Guide, collaborate, and support users in optimizing ML pipelines, by becoming an expert on the Databricks platform.
- Mentor and engage ML/AI practitioners at Ubisoft, sharing knowledge and best practices in ML Ops.
- Participate in proof-of-concept projects, advancing knowledge of new ML technologies.
Qualifications
- 3 to 5 years of complex experience and in-depth expertise related to the position.
- Team player and excellent organizational, interpersonal and communication skills.
- Passion for leveraging data science in problem solving.
- Ability to assess problems quickly, both qualitatively and quantitatively.
- Ability to navigate between the big picture and the details of Data Science / ML Engineering, with a strong programming background with Java, Scala or Python.
- Experience in Machine Learning, Data Science, or a related field, with a focus on improving model and data quality, and the proven ability to build automated AI processes and manage large-scale data pipelines.
- Experience in deploying models, setting up model validation, and operationalizing AI/ML systems at scale in production environments.
- Experience with ML concepts, tools such as MLFlow, and frameworks/libraries like Scikit-learn, PyTorch, XGBoost. Experience with Databricks is an asset.
- Knowledge of Big Data—Spark, PySpark, data engineering, and pipeline architecture technologies is essential.
- Have a foundation in software engineering principles and proficiency in DevOps tools and practices
- Bachelor's or Master's degree in Computer Science, Computer Engineering, or Software or equivalent.
Additional Information
We embrace a hybrid work model helping you stay connectedwith your team and aligned with business priorities, while giving you the opportunity to maintain your work-life balance.Note, that some roles are fully office-based and are not eligible for hybrid work.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Architecture Big Data Computer Science Databricks Data pipelines Data quality DevOps Engineering Java Machine Learning MLFlow ML models Pipelines PySpark Python PyTorch Scala Scikit-learn Security Spark XGBoost
Perks/benefits: Career development
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