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Product Manager Machine Learning Jobs in Quebec (NOW HIRING)

Bentley Systems

Senior Product Manager

Quebec, QC

As a Senior Product Manager, you'll own the vision, strategy, and roadmap for one or more products ... A growth mindset approach, actively seeking feedback and learning opportunities to overcome ...

Bentley Systems

Senior Product Manager

Quebec, QC

As a Senior Product Manager, you'll own the vision, strategy, and roadmap for one or more products ... A growth mindset approach, actively seeking feedback and learning opportunities to overcome ...

Lever Demo 2

Jr. Product Manager

Montreal, QC · On-site

We're looking for a stellar Junior Technical Product Manager to help build and manage the ... A thoughtful problem solver dedicated to constantly learning and improving * Comfortable leading ...

Quandela

AI scientist for Quantum Computing

Montreal, QC · On-site

... machine learning. You will work on research with colleagues across AI, quantum algorithms, software, product and hardware. The Montreal team is a central part of Quandela's AI activities. This role ...

Ubisoft

Software Engineer - MLOPS

Montreal, QC

Deploy and manage scalable cloud infrastructures * Improve platform quality and reliability ... Collaborate closely with data and machine learning specialists to bring models into production ...

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All JobsProduct Machine Learning JobsProduct Manager Machine Learning JobsProduct Manager Machine Learning Jobs in Quebec

Product Manager Machine Learning information

See Quebec salary details

$27K

$136.8K

$236K

How much do product manager machine learning jobs pay per year?

As of Aug 7, 2026, the average yearly pay for product manager machine learning in Quebec is $136,798.00, according to ZipRecruiter salary data. Most workers in this role earn between $104,500.00 and $169,000.00 per year, depending on experience, location, and employer.

How does a product manager machine learning typically collaborate with data scientists and engineering teams?

Product Managers in Machine Learning work closely with both data scientists and engineering teams to translate business objectives into viable AI-driven products. They facilitate communication by defining clear requirements, prioritizing features, and ensuring that the technical roadmap aligns with user needs and company strategy. Regular meetings, progress reviews, and shared documentation are common practices to keep everyone aligned. This cross-functional collaboration is essential for addressing feasibility, optimizing models, and delivering successful products on schedule.

What does a product manager machine learning do?

A Product Manager for Machine Learning oversees the development and deployment of machine learning products or features. They work closely with data scientists, engineers, and business stakeholders to identify opportunities where machine learning can deliver value, define product requirements, and guide projects from conception to launch. Their responsibilities include setting the product vision, prioritizing features, ensuring alignment with business goals, and evaluating the impact of machine learning solutions. They also help bridge the gap between technical teams and non-technical stakeholders by translating complex concepts into actionable plans.

What is the difference between Product Manager Machine Learning vs Data Scientist?

AspectProduct Manager Machine LearningData Scientist
Primary FocusOverseeing ML product development, strategy, and deploymentAnalyzing data, building models, and deriving insights
Required SkillsProduct management, ML understanding, cross-functional collaborationStatistics, programming, data analysis
Work EnvironmentProduct teams, engineering, business stakeholdersData analysis teams, research, engineering
Common CertificationsProduct management certifications, ML coursesData science certifications, programming skills

While both roles involve machine learning, Product Manager Machine Learning focuses on guiding ML products from conception to deployment, working closely with engineering and business teams. Data Scientists primarily analyze data and develop models to extract insights. The roles complement each other but differ in their core responsibilities and skill sets.

What are the key skills and qualifications needed to thrive as a product manager machine learning?

To thrive as a Product Manager, Machine Learning, you need a solid understanding of product lifecycle management, data analytics, and machine learning concepts—often supported by a technical degree and relevant experience. Familiarity with tools like Python, SQL, JIRA, and machine learning frameworks, as well as certifications such as PMP or Agile, is highly beneficial. Outstanding communication, stakeholder management, and problem-solving skills help you bridge the gap between technical teams and business objectives. These abilities are crucial to successfully guide ML products from ideation to launch, ensuring they deliver real value and align with organizational goals.
What are popular job titles related to Product Manager Machine Learning jobs in Quebec? For Product Manager Machine Learning jobs in Quebec, the most frequently searched job titles are:
What job categories do people searching Product Manager Machine Learning jobs in Quebec look for? The top searched job categories for Product Manager Machine Learning jobs in Quebec are:
Product Manager Machine Learning jobs near you
Infographic showing various Product Manager Machine Learning job openings in Quebec as of August 2026, with employment types broken down into 88% Full Time, 11% Part Time, and 1% Contract. Highlights an 84% Physical, 3% Hybrid, and 13% Remote job distribution, with an average salary of $136,798 per year, or $65.8 per hour.

Applied Machine Learning Scientist II (ATH # 5215)

Td

Montreal, QC

CA$125K - CA$154K/yr

Full-time

Posted 3 days ago

New

Job description

Work Location:

Toronto, Ontario, Canada

Hours:

37.5

Line of Business:

Analytics, Insights, & Artificial Intelligence

Pay Details:

$125,500 - $154,000 CADThe pay details posted reflect a temporary market premium specific to this role that is reassessed annually.

TD is committed to providing fair and equitable compensation opportunities to all colleagues. Growth opportunities and skill development are defining features of the colleague experience at TD. Our compensation policies and practices have been designed to allow colleagues to progress through the salary range over time as they progress in their role. The base pay actually offered may vary based upon the candidate's skills and experience, job-related knowledge, geographic location, and other specific business and organizational needs.

As a candidate, you are encouraged to ask compensation related questions and have an open dialogue with your recruiter who can provide you more specific details for this role.

Job Description:

*Department Overview

TD Model Validation (MV) group is responsible for the independent validation and approval of models used forAgentic AI,Generative AI, Natural Language Processing (NLP), credit, fraud, and marketing models. The Artificial Intelligence/Machine Learning (AI/ML) MV team is responsible for the validation of all AI/ML models used across the Bank for various use cases.

*Job Description

The position reports to SeniorApplied Machine Learning Scientist(Generative AI),inthe AI/ML Model Validation team and is primarily focused on the validation and review of Generative AI and Deep Learning models.

Detailed accountabilities include:

  • Validate (review, test, and provide effective challenge) AI/ML models, particularly Generative AI and Deep Learning models.

  • Conduct R&Din the area ofGenAI / Agentic AI / LLM evaluation, testing, explainability.

  • Stay up to date with advancements in the field of Generative AI including major publications, important Large Language Models (LLMs), evaluation metrics, technology stacks, and datasets.

  • Maintain full professional knowledge of techniques and developments in the field of AI/ML and share knowledge with business partners and senior management.

  • Develop/implement AI/ML model validation methodologies and standards. Ensure that the validation methodologies and standards are in line withindustrybest practices and address regulatory and audit requirements.

  • Develop and apply a variety of statistical tests and modeling techniques to identify/recommend improvements to models and undertake related initiatives. Implement benchmark models as applicable.

  • Communicate findings and recommendations to both technical and non-technical stakeholders.

The position involves working effectively with different internal partners suchas AI2, Layer6, P&T, and FCRM.

*Job Requirements

  • Strong quantitative skills with an advanced degree in one or more of the following areas: computer science, machine learning, engineering, statistics, mathematics, or physics.

  • Proven experience as Generative AI Scientist, Machine Leaning Scientist, or a similar role.

  • Ability to work independently and collaboratively in a fast-paced, dynamic environment. Great time management and multitasking skills with minimal supervision.

  • Experience with and strong knowledge of AI/ML methodologies including Generative AI, Agentic AI, Deep Learning, modern Natural Language Processing (NLP), Retrieval-Augmented Generation (RAG), Transformers, Diffusion models

  • Experience with Deep Learning and Generative AI technology stacks and libraries such asPyTorch,LangChain,HuggingFace,PromptFlow, etc.

  • Motivated to stay up to date with the latest advancements in Generative AI, Prompt Engineering, Machine Learning, and Cloud technologies.

  • Proficient in scripting/programming language-Python.

  • Familiarity with cloud platforms (e.g., Azure, AWS).

  • Familiarity with Data Structures, Algorithm design, and principles of Object-Oriented Programming (OOP).

  • Knowledge of machine learning explain-ability/interpretability algorithms.

  • Excellent verbal and written communication skills. The position requires writing clean technical reports.

* Nice to have qualifications

  • Publications in the relevant conference and journalsisa plus.

  • Ability to implement AI/ML algorithms from academic research papers is a plus.

  • Knowledge of SQL and database systems.

Who We Are:

TD is one of the world's leading global financial institutions and is the fifth largest bank in North America by branches/stores. Every day, we strive to make every interaction, product, and experience remarkably human and refreshingly simple for over 27 million households and businesses in Canada, the United States and around the world. More than 95,000 TD colleagues bring their skills, talent, and creativity to foster deeper relationships, ensure disciplined execution, and build a simpler, faster banking experience. TD is deeply committed to being a leader in client experience, that is why we believe that all colleagues, no matter where they work, are client facing. Together, we are reimagining what banking can be for our clients, colleagues and communities.

Our Total Rewards Package
Our Total Rewards package reflects the investments we make in our colleagues to help them and their families achieve their financial, physical, and mental well-being goals. Total Rewards at TD includes a base salary, variable compensation, and several other key plans such as health and well-being benefits, savings and retirement programs, paid time off, banking benefits and discounts, career development, and reward and recognition programs. Learn more

Additional Information:
We're delighted that you're considering building a career with TD. Through regular development conversations, training programs, and a competitive benefits plan, we're committed to providing the support our colleagues need to thrive both at work and at home.

Please be advised that this job opportunity is subject to provincial regulation for employment purposes. It is imperative to acknowledge that each province or territory within the jurisdiction of Canada may have its own set of regulations, requirements.


Colleague Development

If you're interested in a specific career path or are looking to build certain skills, we want to help you succeed. You'll have regular career, development, and performance conversations with your manager, as well as access to an online learning platform and a variety of mentoring programs to help you unlock future opportunities.

If you're passionate about helping clients and building deep, lasting relationships, TD offers diverse career paths where you can grow your expertise and make a meaningful impact.

We're committed to your success and foster a respectful workplace where diverse perspectives are valued, everyone has fair opportunities to grow, and you can unlock your full potential to achieve your career goals. Here at TD, we hire and develop the best.

Training & Onboarding
We will provide training and onboarding sessions to ensure that you've got everything you need to succeed in your new role.

Interview Process
We'll reach out to candidates of interest to schedule an interview. We do our best to communicate outcomes to all applicants by email or phone call.


Accommodation
Your accessibility is important to us. Please let us know if you'd like accommodations (including accessible meeting rooms, captioning for virtual interviews, etc.) to help us remove barriers so that you can participate throughout the interview process.
We look forward to hearing from you!

Language Requirement (Quebec only):

Ce poste n'exige pas la maitrise d'une langue autre que le francais.

Apply