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Machine Learning Engineer

Build the AI (artificial intelligence) systems that actually run. Heavy math, heavy code, and Canada is a world centre for it.

Typical pay
$96,000a year
Time to qualify
4 to 8 yearsafter high school
Demand
Moderate
Licence needed
Nono licence to hold

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  1. 1.MoneyWhat you earn and what it costs to get there.4 screens
  2. 2.EducationThe exact path from high school to qualified.4 screens
  3. 3.OptionalThings you don't need, but that help.3 screens
  4. 4.ExtrasDay to day, pros and cons, where you'd work.4 screens
  5. 5.FactoidsThings people don't tell you.3 screens

Quick answers

How much does a machine learning engineer make in Canada?

The median pay is about $96,000 a year. Across everyone in the job it runs from about $62,000 at the lower end to about $145,000 at the upper end. The source is listed under Sources at the end of this page.

How long does it take to become a machine learning engineer in Canada?

4 to 8 years after high school, on the usual route.

What does it cost to become a machine learning engineer?

$600 to $90,000 all in for tuition, fees, exams and kit. Living costs are not counted.

Do you need a licence to work as a machine learning engineer in Canada?

No. There is no licence to hold, though many employers still ask for training or a certificate.

What is the job outlook for a machine learning engineer in Canada?

Moderate demand nationally, from government outlook data. Demand varies by region, so check your area.

Or read the whole thing here

Machine Learning Engineer salary in Canada

What you earn and what it costs to get there.

What machine learning engineers make

Median

$96,000

Lower end

$62,000

Upper end

$145,000

Job Bank's national median is $46.15 an hour, about $96,000 a year at 40 hours a week. The lower end ($30) and upper end ($69.74) are the bottom and top of the wage range for everyone in the group, which Job Bank pools with data scientists (NOC, the National Occupational Classification, code 21211). Few people start straight from a bachelor's: most have a master's or a couple of years as a developer first.

Where pay is highest

$48.08 an hour

The median in British Columbia, about $100,000 a year

Ontario is close behind at $47.69. New Brunswick has the lowest median, $39.32.

What it costs to get there

Bachelor's degree in computer science, math or engineering (4 years)
$6,000 to $15,000 a year
Master's degree (1 to 2 years)
$10,000 to $30,000 total, often partly funded by research assistantships
PhD (4 to 6 years, optional)
Usually funded: tuition covered plus a stipend to live on
Hardware and tools
Most software costs nothing. Cloud computing credits are often given to students at no cost.

Roughly, all in

$600 to $90,000

Tuition, fees, exams and kit. Not rent, food or travel

The low end is teaching yourself with no-cost software and a small amount of paid cloud computing time, then moving across from a job beside it, usually software developer or data analyst, at a company that is starting to build these systems. The high end is an expensive four year degree plus a master's degree, which most job advertisements still ask for. This is the hardest cheap door on this list, because without the degree there is no credential to point at and you need finished, working projects that other people actually use before anyone will interview you.

Vector, Mila and Amii, the three national AI (artificial intelligence) institutes, fund scholarships and internships for graduate students in this field.

Perks common in this field

  • Stock options or RSUs (restricted stock units, company shares you receive over time)

    Part of total pay at many tech companies and AI (artificial intelligence) startups.

  • Remote or hybrid work

    Normal.

  • Research time and conferences

    Employers send engineers to conferences and some allow time to publish.

  • Signing bonuses

    Common when a company is competing for a scarce specialist.

How to become a machine learning engineer in Canada

The exact path from high school to qualified.

The path to becoming a machine learning engineer, step by step

The deepest math of any job on this site outside of engineering and physics, plus strong programming.

  1. 1

    High school

    Grades 11 and 12

    Every math course available, especially Calculus and Vectors. Computer science. Start Python now.

  2. 2

    Bachelor's degree

    4 to 5 years with co-op

    Computer science, math, statistics or computer engineering. Waterloo, Toronto, UBC (University of British Columbia), McGill, Montreal and Alberta all have strong AI (artificial intelligence) groups. Take linear algebra, probability and any machine learning course offered.

  3. 3

    Master's degree

    1 to 2 years

    Most job ads ask for one. Thesis-based master's degrees at Canadian universities are often funded, and the national AI institutes offer scholarships.

  4. 4

    Internships and research

    During school

    Co-op at a bank's AI team, a startup, or a lab affiliated with Vector, Mila or Amii. A published paper or a well-known open source contribution counts for a lot.

  5. 5

    First job or PhD

    After the master's

    Machine learning engineer at a company, or a PhD if you want a research scientist title.

High school courses that help you become a machine learning engineer

  • Calculus and Vectors

    Neural networks are calculus and linear algebra.

  • Advanced Functions and Data Management

    Probability and statistics underpin everything.

  • Computer science

    You will write code every day.

  • Physics

    Same thinking style: models of the world, tested against data.

Time and money, at a glance

Years after high school
4 to 8
Admission average (computer science degree)
From a 70% minimum at some schools to the low to mid 90s at Waterloo and Toronto
Total tuition
$35,000 to $90,000, less if graduate study is funded
Paid while training?
Yes, on co-op terms and through graduate funding

Not regulated, but watch the title

No licence or exam. But the word engineer is protected by provincial engineering regulators in most of Canada, so companies often use machine learning developer, ML (machine learning) scientist or AI (artificial intelligence) developer for people without an engineering licence. Alberta changed its law in 2023 so anyone may use the exact title software engineer, but that is the only title it freed. Nobody will stop you doing the work; the title is the only issue.

Quebec route. In Quebec? The route is different. 1 more card.

The path in Quebec

Quebec students reach university through a 2 year DEC (Diploma of College Studies), and Montreal's Mila institute is a common place to do the graduate degree.

  1. 1

    Finish Secondary V

    Age 16 or 17

    Take the strongest math you can. Universities expect CEGEP (public college) calculus and linear algebra, which build on it.

  2. 2

    Pre-university DEC (Diploma of College Studies)

    2 years

    A 2 year CEGEP (public college) program with calculus and linear algebra, usually science. No tuition for full-time Quebec residents.

  3. 3

    Bachelor's in computer science

    3 years

    McGill credits your CEGEP year, so its degree takes 3 years (90 credits). Concordia also takes some 3 year technical DECs (Diplomas of College Studies) in computing.

  4. 4

    Master's, often through Mila

    Optional

    Mila, the Quebec AI (artificial intelligence) institute, places graduate students with professors at Université de Montréal, McGill and Polytechnique Montréal. Requests run 15 October to 1 December, alongside a separate university application.

  5. 5

    Mind the title

    Any time

    Only members of the OIQ (Ordre des ingénieurs du Québec, the Quebec order of engineers) may use "engineer". Membership needs an accredited engineering degree, not computer science.

What helps you get ahead as a machine learning engineer

Things you don't need, but that help.

Specialties that open doors

  • Large language models

    Training, tuning and serving the models behind chat tools. The hottest specialty since 2023.

  • MLOps (machine learning operations)

    The DevOps of AI (artificial intelligence): getting models into production reliably and cheaply. Scarce skill.

  • Computer vision

    Self-driving, medical imaging, factory inspection.

  • Reinforcement learning

    Alberta is a world centre for it, through Amii and the University of Alberta.

Nice-to-haves

  • Open source contributions

    PyTorch, Hugging Face and the tools around them are open. Contributing gets you noticed.

  • Kaggle competitions

    A top finish is a strong signal for your first job.

  • A cloud certificate

    AWS (Amazon Web Services) has a Machine Learning Engineer Associate exam. Employers like it.

The research route

Canada's three national AI (artificial intelligence) institutes, Vector in Toronto, Mila in Montreal and Amii in Edmonton, are among the most respected in the world. Mila alone has more than 1,400 researchers. A PhD through one of them opens research scientist jobs at the big labs. It also takes 4 to 6 more years.

What being a machine learning engineer is really like

Day to day, pros and cons, where you'd work.

What a machine learning engineer does day to day

Stand-up with the team, then experiments: preparing training data, tuning a model, waiting for it to train, reading the results. Writing the code that serves the model inside a product and monitoring it once it is live. Reading a new paper because the field changed again last week. Meetings with product managers about what the model is allowed to get wrong. Compute costs are always a topic.

The honest pros and cons of being a machine learning engineer

The good

  • Job Bank's upper end is about $145,000 a year
  • Canada is a genuine world centre, with funded labs in three cities
  • Work on problems that are changing every industry
  • Remote and hybrid work are normal

The hard parts

  • Long education: most jobs want a master's, research wants a PhD
  • Hard math, and the field moves so fast that last year's skills date
  • Hype cycles: hiring surges and freezes with investor mood
  • Much of the daily work is data plumbing, not inventing intelligence

Work life

Typical hours
40 a week, more at startups
Remote work
Common
Physical demand
Low
Unionized
No

Things nobody tells you about being a machine learning engineer

Things people don't tell you.

A Nobel Prize for a Toronto professor

Geoffrey Hinton of the University of Toronto shared the 2024 Nobel Prize in Physics for foundational work on neural networks. His Montreal colleague Yoshua Bengio, who founded Mila, shared the Turing Award, computing's top prize, in 2019.

The first national AI strategy in the world

Canada launched the Pan-Canadian AI (artificial intelligence) Strategy in 2017 with $125 million. Its second phase, from 2021 to 2031, got $443.8 million, plus $174 million more in 2024.

Deep learning was kept alive in Canada

In the 2000s, when most of the world had given up on neural networks, a small group funded by CIFAR (the Canadian Institute for Advanced Research) kept working on them in Toronto and Montreal. Mila, founded by Bengio in 1993, now counts more than 1,400 researchers.

How a machine learning engineer compares

Every list is built from the same numbers shown above, so you can see where this career sits next to the others.

More tech careers in Canada

Data and AI first, then the rest of the field. See every career in tech.

Read more about it

Where these numbers come from

Last checked October 2026. Pay figures are typical full-time annual amounts in Canadian dollars, based on Government of Canada Job Bank wage data and published salary grids. They vary by province, employer and experience. Tuition is for domestic students. How every figure on this site is sourced and checked.

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