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Senior Machine Learning Engineer Jobs in Quebec (NOW HIRING)

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 ...

Senior Data Scientist Montréal, Canada The Sr. Data Scientist will conduct detailed analysis of ... Experience with developing Machine Learning and statistical models. * Excellent programming skills ...

Work closely with machine learning engineers and data engineers to design, build, and test models. * Develop efficient and scalable algorithms for training and inference of generative models ...

Solid knowledge of applied Machine Learning, Deep Learning, Large Language Models * Solid cloud ... Data Engineering : ETL/ELT Pipelines, Apache Spark Nice-to-Have * Experience in customer analytics ...

Design, develop, and optimize machine learning models for demand forecasting, inventory ... Engineer advanced features including promotions, seasonality, holidays, stockouts, lag variables ...

Role Nous recherchons un(e) Data Scientist Senior pour rejoindre une equipe hautement collaborative ... Ce poste se situe a l'intersection de la Data Science, du Machine Learning et de l'ingenierie, avec ...

... analytics, engineering, product) on high-impact end-to-end use cases (anomaly detection ... Use machine learning and advanced statistical methods to identify trends and patterns in complex ...

Showing results 41-60

Senior Machine Learning Engineer information

What does a senior machine learning engineer do?

A Senior Machine Learning Engineer designs, develops, and implements machine learning models to solve complex problems. They are responsible for selecting appropriate algorithms, preprocessing data, and optimizing model performance. Additionally, they collaborate with data scientists, software engineers, and product teams to integrate machine learning solutions into production systems. Senior engineers also mentor junior team members and contribute to setting technical direction for machine learning projects.

What are some common challenges senior machine learning engineers face when deploying models to production, and how can they be addressed?

Senior Machine Learning Engineers often encounter challenges related to model scalability, maintaining performance in real-world scenarios, and ensuring reliable integration with existing systems. Addressing these challenges typically involves thorough testing, implementing robust monitoring for model drift, and collaborating closely with DevOps and software engineering teams to streamline deployment pipelines. Staying updated on best practices in MLOps and adopting tools for automated deployment and monitoring can greatly improve the reliability and efficiency of production models.

What are the key skills and qualifications needed to thrive as a senior machine learning engineer, and why are they important?

To thrive as a Senior Machine Learning Engineer, you need advanced knowledge of machine learning algorithms, statistical modeling, and programming languages like Python or Java, typically supported by a degree in computer science or a related field. Experience with frameworks and tools such as TensorFlow, PyTorch, scikit-learn, and cloud platforms, as well as familiarity with version control and CI/CD systems, is essential. Strong problem-solving, communication, and leadership skills help you collaborate effectively and mentor junior team members. These capabilities are crucial for designing scalable ML solutions and driving impactful results within complex, dynamic projects.

What is the difference between Senior Machine Learning Engineer vs Data Scientist?

AspectSenior Machine Learning EngineerData Scientist
Required CredentialsBachelor's/Master's in CS, ML, or related; experience with ML frameworksBachelor's/Master's in CS, Statistics, or related; strong analytical skills
Work EnvironmentDevelops and deploys ML models in production systemsAnalyzes data, builds models, and provides insights
Industry UsageTech, finance, healthcare, e-commerceResearch, finance, marketing, tech

While both roles require strong technical skills and knowledge of machine learning, Senior Machine Learning Engineers focus more on deploying scalable ML solutions in production environments, whereas Data Scientists primarily analyze data and develop models for insights. The roles often overlap but differ in their core responsibilities and focus areas.

What are the most commonly searched types of Machine Learning Engineer jobs in Quebec?

The most popular types of Machine Learning Engineer jobs in Quebec are:

What are popular job titles related to Senior Machine Learning Engineer jobs in Quebec?

For Senior Machine Learning Engineer jobs in Quebec, the most frequently searched job titles are:

What job categories do people searching Senior Machine Learning Engineer jobs in Quebec look for?

The top searched job categories for Senior Machine Learning Engineer jobs in Quebec are:

What cities in Quebec are hiring for Senior Machine Learning Engineer jobs?

Cities in Quebec with the most Senior Machine Learning Engineer job openings:

Infographic showing various Senior Machine Learning Engineer job openings in Quebec as of August 2026, with employment types broken down into 1% As Needed, 78% Full Time, 20% Part Time, and 1% Contract. Highlights an 85% Physical, 3% Hybrid, and 12% Remote job distribution.

Software Engineer - MLOPS

Ubisoft

Montreal, QC

Full-time

Re-posted 25 days ago


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

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