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Senior Machine Learning Engineer Jobs in Quebec (NOW HIRING)

Votre profil Minimum de 5 années d'expérience dans un rôle d'AI Engineer, Machine Learning Engineer, MLOps Engineer ou similaire. Solide expérience avec Google Cloud Platform (GCP). Expérience ...

Votre profil Minimum de 5 années d'expérience dans un rôle d'AI Engineer, Machine Learning Engineer, MLOps Engineer ou similaire. Solide expérience avec Google Cloud Platform (GCP). Expérience ...

Votre profil Minimum de 5 années d'expérience dans un rôle d'AI Engineer, Machine Learning Engineer, MLOps Engineer ou similaire. Solide expérience avec Google Cloud Platform (GCP). Expérience ...

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 ...

Experience in practical machine learning applications and development * Ability to develop ... Programming and use of tools related to our area of practice, such as Python, PyTorch, Scikit-learn ...

Experience in practical machine learning applications and development * Ability to develop ... Programming and use of tools related to our area of practice, such as Python, PyTorch, Scikit-learn ...

Apply machine learning and AI methods to support classification, scoring, summarization, pattern ... Collaborate with AI Scientists, AI Engineers, Analytics Engineers, Data Engineers, and Architects ...

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

... analytics, machine learning, generative AI, agentic AI, and computer vision directly within ... Engineer advanced features including promotions, seasonality, holidays, stockouts, lag variables ...

Showing results 41-60

Senior Machine Learning Engineer information

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 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 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 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, 76% Full Time, 20% Part Time, 1% Temporary, and 2% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution.

Sr. Manager, AI, Innovation & Operation

McKesson

Montreal, QC • On-site, Remote

Full-time

Posted 6 days ago


McKesson rating

7.9

Company rating: 7.9 out of 10

Based on 209 frontline employees who took The Breakroom Quiz

47th of 86 rated pharmaceutical


Job description

McKesson is an impact-driven, Fortune 10 company that touches virtually every aspect of healthcare. We are known for delivering insights, products, and services that make quality care more accessible and affordable. Here, we focus on the health, happiness, and well-being of you and those we serve - we care.

What you do at McKesson matters. We foster a culture where you can grow, make an impact, and are empowered to bring new ideas. Together, we thrive as we shape the future of health for patients, our communities, and our people. If you want to be part of tomorrow's health today, we want to hear from you.

About the Role

McKesson is seeking a Senior Manager, AI , Innovation & Operation to lead a high-impact analytics function focused on enterprise data, machine learning, generative AI, and executive-ready business insights. In this role, you will set analytics strategy, guide managers and teams, and deliver scalable solutions that improve decision-making, operational performance, and business outcomes.

This role is ideal for a hands-on data and AI leader with experience across the full machine learning lifecycle, modern cloud data platforms, and responsible AI governance. You will partner with business, technology, and executive stakeholders to shape analytics roadmaps, strengthen data practices, and accelerate adoption of advanced analytics, AI, and automation across the organization.

What You'll Do
  • Lead development and execution of analytics, AI, and data strategy aligned to enterprise priorities.
  • Manage analytics leaders and teams delivering forecasting, performance insights, machine learning models, and executive dashboards.
  • Oversee end-to-end delivery of complex, cross-functional data science, analytics, and AI initiatives.
  • Drive adoption of modern data and AI platforms, including Azure AI Foundry, Snowflake, Databricks, and related cloud technologies.
  • Guide teams through the full ML lifecycle, including exploration, feature engineering, model development, deployment, monitoring, and improvement.
  • Establish governance practices for data quality, model risk, responsible AI, regulatory compliance, DevOps, and operational controls.
  • Partner with business and technology leaders to prioritize investments, optimize tools, and mature analytics capabilities.
  • Build an inclusive, high-performing team culture through coaching, talent development, collaboration, and change leadership.
Basic Requirements
  • 9+ years of experience in analytics, data science, machine learning, AI, business intelligence, or a related field, including people leadership or management experience.
  • Bachelor's degree in Computer Science, Data Science, Engineering, Statistics, Analytics, Information Systems, or equivalent experience.
  • Hands-on experience with modern data and AI stacks, including cloud platforms, data engineering, analytics, and AI/ML tools.
  • Experience leading teams through the full machine learning lifecycle from use case definition through production deployment and monitoring.
  • Experience with at least one major enterprise data or AI platform such as Azure AI Foundry, Snowflake, Databricks, Azure ML, or similar technologies.
  • Demonstrated experience leading complex analytics, AI, data platform, or enterprise reporting initiatives.
  • Strong communication skills with experience translating technical insights into executive-level recommendations.
  • Experience establishing or operating data governance, model governance, DevOps, or compliance practices.
Preferred Skills/Experience
  • Experience with generative AI architectures, large language models, retrieval-augmented generation, prompt engineering, or AI solution design.
  • Experience leading AI/ML programs in regulated, healthcare, supply chain, distribution, or enterprise technology environments.
  • Familiarity with MLOps, CI/CD, model monitoring, data observability, and production AI operating models.
  • Experience managing budgets, vendor relationships, technology investments, or analytics platform roadmaps.
  • Experience building executive dashboards and analytics products using tools such as Power BI, Tableau, or similar platforms.
  • Ability to influence cross-functional stakeholders and drive adoption of new analytics, AI, and governance practices.
  • Demonstrated commitment to inclusive leadership, coaching, and talent development.
Travel / Work Environment / Physical Requirements
  • Work model may be remote, hybrid, or office-based depending on business and team needs.
  • Occasional travel may be required for team, stakeholder, or business meetings.
  • Role requires regular use of a computer and collaboration tools for extended periods

We are proud to offer a competitive compensation package at McKesson as part of our Total Rewards. This is determined by several factors, including performance, experience and skills, equity, regular job market evaluations, and geographical markets. The pay range shown below is aligned with McKesson's pay philosophy, and pay will always be compliant with any applicable regulations. In addition to base pay, other compensation, such as an annual bonus or long-term incentive opportunities may be offered. For more information regarding benefits at McKesson, pleaseclick here.

Our Base Pay Range for this position

$102,500 - $136,700

McKesson has become aware of online recruiting-related scams in which individuals who are not affiliated with or authorized by McKesson are using McKesson's (or affiliated entities, like CoverMyMeds or RxCrossroads) name in fraudulent emails, job postings or social media messages. In light of these scams, please bear the following in mind:
McKesson Talent Advisors will never solicit money or credit card information in connection with a McKesson job application.


McKesson Talent Advisors do not communicate with candidates via online chatrooms or using email accounts such as Gmail or Hotmail. Note that McKesson does rely on a virtual assistant (Gia) for certain recruiting-related communications with candidates.

McKesson job postings are posted on our career site: careers.mckesson.com.

McKesson is an Equal Opportunity Employer

McKesson provides equal employment opportunities to applicants and employees, without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability, age, genetic information, or any other legally protected category. For additional information on McKesson's full Equal Employment Opportunity policies, visit our Equal Employment Opportunity page.

McKesson is committed to being an Equal Employment Opportunity Employer and offers opportunities to all job seekers including job seekers with disabilities. If you need a reasonable accommodation to assist with your job search or application for employment, please contact us by sending an email to (United States) Disability_Accommodation@McKesson.com or (Canada) Accessibility@mckesson.ca. Resumes or CVs submitted to this email box will not be accepted.

Join us at McKesson!


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