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Machine Learning Engineer Jobs in Quebec (NOW HIRING)

Coveo

Senior II Applied Scientist (NLP)

Montreal, QC · On-site

Collaborate closely with machine learning developers and the machine learning platform team to accelerate research and innovation cycles. * Act as a technical reference within the team, guiding ...

Apply Early

Coveo

Senior II Applied Scientist (NLP)

Montreal, QC · On-site

Collaborate closely with machine learning developers and the machine learning platform team to accelerate research and innovation cycles. * Act as a technical reference within the team, guiding ...

Apply Early

Maya HTT

AI Presales Engineer

Montreal, QC

Our team delivers extensive engineering and CAE simulation expertise along with cutting-edge digitalization solutions, such as AI, machine learning, IIoT, operational technologies, and Industry 4.0.

Maya HTT

AI Presales Engineer

Montreal, QC · On-site

Our team delivers extensive engineering and CAE simulation expertise along with cutting-edge digitalization solutions, such as AI, machine learning, IIoT, operational technologies, and Industry 4.0.

Apply Early

Desjardins Group

Data internship, Fall 2026

Levis, QC · Hybrid

Help implement continuous integration and deployment (CI/CD) pipelines for machine learning models * Develop and maintain application programming interfaces (APIs) and software development kits (SDKs ...

TELUS

Staff Applied AI/ML Scientist

Montreal, QC

Expertise in machine learning frameworks such as TensorFlow, Pytorch, and Keras * Strong understanding of software and AI development lifecycles, with experience in DevOps and MLOps practices

Industrial Alliance Pacific

Data Engineer

Quebec, QC · Hybrid

Developing, testing, deploying, and industrializing machine learning and AI models in cloud environments (Azure, Snowflake, Databricks). * Implementing and maintaining DevOps and MLOps practices ...

Industrial Alliance Pacific

Data Engineer

Montreal, QC · Hybrid

Developing, testing, deploying, and industrializing machine learning and AI models in cloud environments (Azure, Snowflake, Databricks). * Implementing and maintaining DevOps and MLOps practices ...

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All JobsMachine Learning Engineer JobsMachine Learning Engineer Jobs in Quebec

Machine Learning Engineer information

What engineers make $500,000?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data science, and often working in high-demand industries or companies can earn $500,000 or more annually. Compensation typically includes base salary, bonuses, and stock options, especially in tech giants or startups with significant funding.

What do machine learning engineers do?

Machine learning engineers develop algorithms and models that enable computers to learn from data and make predictions or decisions. They often work with large datasets, use programming languages like Python or Java, and utilize tools such as TensorFlow or PyTorch to build, test, and deploy machine learning systems in production environments.

What are Machine Learning Engineers?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models and systems. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, production-ready solutions. Their responsibilities include data preprocessing, model selection, algorithm implementation, and optimizing models for performance and efficiency. Machine Learning Engineers often collaborate with data scientists, software developers, and other stakeholders to integrate AI technologies into products and services.

What are the key skills and qualifications needed to thrive as a Machine Learning Engineer, and why are they important?

To thrive as a Machine Learning Engineer, you need strong programming skills (particularly in Python), a solid background in mathematics and statistics, and a degree in computer science or a related field. Experience with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and cloud platforms is typically required. Problem-solving ability, effective communication, and adaptability are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies ensure the development, deployment, and continual improvement of machine learning systems that drive business value.

Which 5 jobs will survive AI?

Machine Learning Engineers are likely to continue to be in demand as AI advances, as they develop and refine algorithms, models, and systems. Roles that require complex problem-solving, creativity, and domain expertise—such as healthcare professionals, data scientists, software developers, cybersecurity specialists, and AI ethics officers—are also expected to persist due to their reliance on human judgment and specialized knowledge. These jobs often involve skills that are difficult for AI to fully replicate or replace.

What Does a Machine Learning Engineer Do?

A machine learning engineer maintains production systems and often works with other engineers. In this career, you work with software development methodology, use modern software development tools, and use agile practices. You also play a role in software design and architecture, so you may occasionally work with a programmer. An engineer may help to predict how a model should perform or seek out regression issues by using different test types and algorithms. To fulfill your duties and responsibilities, you work on a computer and use an array of skills and programs to carry out these tests.

What engineers make $300,000 a year?

Senior machine learning engineers and data scientists with extensive experience, advanced skills in deep learning, and proficiency with tools like TensorFlow or PyTorch can earn $300,000 or more annually, especially in high-cost-of-living areas or top tech companies. Compensation often includes base salary, bonuses, and stock options, reflecting their expertise and impact on business outcomes.

What are some common challenges faced by Machine Learning Engineers when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, maintaining data consistency between training and production environments, and monitoring model performance over time. Integrating models into existing software infrastructure may require collaboration with DevOps and software engineering teams to address issues like latency, version control, and resource allocation. Additionally, ongoing model maintenance is crucial to prevent model drift and ensure that predictions remain accurate as new data becomes available.

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

AspectMachine Learning EngineerData Scientist
CredentialsBachelor's or Master's in CS, Data Science, or related; experience with ML frameworksBachelor's or Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops scalable ML models, deploys algorithms into productionAnalyzes data, builds models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research organizations

While both roles work with data and machine learning, Machine Learning Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights. The roles often overlap but differ in their core responsibilities and focus areas.

More about Machine Learning Engineer jobs
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 Machine Learning Engineer jobs in Quebec? For Machine Learning Engineer jobs in Quebec, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer jobs in Quebec look for? The top searched job categories for Machine Learning Engineer jobs in Quebec are:
What are popular job titles related to Machine Learning Engineer jobs in QC? For Machine Learning Engineer jobs in QC, the most frequently searched job titles are:
Machine Learning Engineer jobs near you
Infographic showing various Machine Learning Engineer job openings in Quebec as of June 2026, with employment types broken down into 1% As Needed, 96% Full Time, 1% Part Time, 1% Temporary, and 1% Contract. Highlights an 86% Physical, 2% Hybrid, and 12% Remote job distribution.

Senior II Applied Scientist (NLP)

Coveo

Montreal, QC • On-site

Full-time

Posted 23 days ago

Be an early applicant

Job description

Shape the future of enterprise AI technology

Do you want to turn cutting-edge natural language processing into products impacting millions of users?

As a Senior II Applied Scientist on Coveo's Knowledge AI team, you will help build the language technologies at the core of our generative artificial intelligence platform.

You'll take on a technical leadership role, influencing our NLP vision while designing, evaluating, and deploying advanced solutions such as retrieval augmented generation pipelines, information retrieval, semantic search, question answering, and agentic systems, always with real-world constraints in mind.

As one of our Senior II Applied Scientists, you will:
  • Design, develop, and optimize modern language-based artificial intelligence solutions, from data and modeling choices to evaluation strategies and production constraints.
  • Apply and serve transformer-based language models at scale, delivering reliable, real-time experiences to enterprise users.
  • Collaborate closely with machine learning developers and the machine learning platform team to accelerate research and innovation cycles.
  • Act as a technical reference within the team, guiding architectural decisions and promoting best practices in applied science.
  • Mentor applied scientists, supporting their growth and helping raise the overall level of expertise within the group.
  • Contribute to research and development processes that foster efficiency, rigor, and a culture of applied science excellence.
  • Share our innovations externally through technical blog posts, presentations, or other thought leadership content.
Here is what will qualify you for the role:
  • A PhD, or a Master's degree with equivalent research experience, in a relevant field such as machine learning, computer science, mathematics, or physics.
  • At least 8 years of industry experience applying modern natural language processing techniques, including deep learning and large language models, to real-world systems at scale.
  • Strong experience designing models and systems that balance performance, user experience, and production realities.
  • Ability to deliver production-grade code that is well-tested, maintainable, and evaluated through rigorous experimentation.
What will make you stand out:
  • Experience in a technical leadership capacity, including mentoring, hiring, roadmap definition, or scientific project planning.
  • Research or applied experience in areas closely related to Coveo's business, such as information retrieval, neural search, semantic search, or question answering.
  • Exposure to more traditional lexical or linguistics-based natural language processing techniques.
  • International work experience and a demonstrated ability to collaborate across cultures and perspectives.

Do you think you can bring this role to life? Or add your own color?
You don't need to check every single box; passion goes a long way and we appreciate that skillsets are transferable.

Send us your application, we want to hear from you!

Join the Coveolife!

We encourage all qualified candidates to apply regardless of, for example, age, gender, disability, gaps in CV, national or ethnic background.
Coveo is committed to providing accessible employment practices. If you require accommodation due to a disability at any point during the recruitment process, please contact HR@Coveo.com to discuss your needs.