Engineering · Canada
Machine Learning Engineer Salary in Toronto, ONCA$111,708–CA$145,092 in 2026
In Toronto, ON, ML engineers occupy the highest-paying tier of individual contributor roles. The technical bar is real — companies want engineers who can go from research prototype to production system — and the pay reflects that: CA$111,708 to CA$145,092 for someone with three to five years of experience. The engineers who negotiate best in this space are those who can speak to model performance metrics, not just engineering metrics.
Machine Learning Engineer Salary in Toronto — 2026 Overview
Entry Level
CA$97,584
0–2 years
Mid-Level
CA$128,400
3–5 years
Senior
CA$166,920
6–10 years
| Experience | Low | Median | High |
|---|---|---|---|
| 0–2 years | CA$85,874 | CA$97,584 | CA$109,294 |
| 3–5 years | CA$111,708 | CA$128,400 | CA$145,092 |
| 6–10 years | CA$145,220 | CA$166,920 | CA$188,620 |
| 11+ years | CA$182,200 | CA$211,860 | CA$241,520 |
Data reflects base salary for Machine Learning Engineers in Toronto, ON, 2026. Figures exclude bonus, equity, and benefits. Sources: market surveys, job postings, and aggregated offer data.
Why Machine Learning Engineer Salaries Are This Level in Toronto
Toronto is Canada's largest tech market and the base for Shopify, which has set a high bar for engineering compensation nationally. Fintech and banking tech (RBC, TD) create consistent demand. Salaries are below US equivalents but competitive in Canadian dollar terms.
Toronto has become very expensive. A one-bedroom condo in downtown or Midtown runs CA$2,200–CA$3,500/month. Ontario's combined federal and provincial income tax rate is meaningful — factor this into your net pay calculation alongside the currency difference from USD-denominated benchmarks.
Top Toronto employers hiring Machine Learning Engineers
Machine Learning Engineer Job Market in Toronto: Demand & Hiring Outlook
Toronto has established itself as a credible engineering hub, with a growing cluster of tech companies that compete seriously for Machine Learning Engineers. Salaries sit meaningfully below tier-one markets like San Francisco or London, but so does the cost of living — making the purchasing power of an engineering salary here competitive. Hiring demand has been steady, and Machine Learning Engineers with strong fundamentals rarely stay on the market long.
What Machine Learning Engineers in Toronto Actually Negotiate For
Base salary is only the starting point. The most experienced negotiators in Toronto push for the full package — and the employers who want you badly enough will move on more than just base.
- Equity
- Research time
- GPU compute budget
- Conference access
- Publication rights
Many Machine Learning Engineers leave CA$15,408–CA$32,100 on the table annually by not negotiating these elements. A signing bonus alone can be worth one to two months' salary — and it doesn't affect your base going forward.
Skills That Command the Highest Machine Learning Engineer Salaries in Toronto
Not all Machine Learning Engineers in Toronto earn the same — and the gap between the lower and upper end of the salary range comes down to specific technical and leadership competencies. These are the skills that consistently push offers toward CA$145,092 and above.
Is your Machine Learning Engineer offer in Toronto fair?
You now have the market range: CA$111,708–CA$145,092. The next step is knowing exactly where your specific offer sits — and getting the word-for-word script to negotiate it. SalaryAsk benchmarks your offer against live market data, builds your personalised strategy, and lets you practice the conversation with a virtual hiring manager.
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Frequently Asked Questions
What is the average Machine Learning Engineer salary in Toronto, ON?
The median Machine Learning Engineer salary in Toronto, ON is CA$128,400 for someone with 3–5 years of experience. Across all experience levels, the range runs from CA$85,874 for entry-level through to CA$241,520 for highly experienced or specialised professionals.
Is CA$111,708–CA$145,092 a good Machine Learning Engineer salary in Toronto?
Yes — for a mid-level Machine Learning Engineer in Toronto, ON, CA$111,708–CA$145,092 represents the market rate in 2026. If your offer falls significantly below CA$111,708, it's worth negotiating or understanding why the company is below the market benchmark. Offers above CA$145,092 typically reflect either a scarce specialisation, a particularly well-funded company, or both.
How much does a Staff ML Engineer / Principal AI Engineer earn in Toronto?
Senior Machine Learning Engineers and people moving into Staff ML Engineer / Principal AI Engineer roles typically earn CA$145,220–CA$241,520 in Toronto, ON. At the most senior levels, total compensation (including equity and bonuses) often substantially exceeds the base salary shown here.
How do I negotiate a Machine Learning Engineer salary in Toronto?
The first step is anchoring to market data — you now know the range is CA$111,708–CA$145,092. The second is understanding your specific leverage: your experience, the company's urgency to hire, and what competing offers or alternatives you have. SalaryAsk walks you through all of this, generates a personalised negotiation strategy, and gives you the exact language to use in the conversation.
Does remote work affect Machine Learning Engineer salaries in Toronto, ON?
It depends on the company's policy. Toronto, ON-based companies that allow full remote work sometimes adjust salaries to local market rates if you relocate — but many still pay the Toronto band (CA$111,708–CA$145,092) regardless of where you work. If you're negotiating a remote arrangement, it's worth explicitly agreeing on whether the salary is tied to your location or to the role's market rate.
What is the difference between a Machine Learning Engineer and a Staff ML Engineer / Principal AI Engineer in terms of pay?
In Toronto, ON, the jump from mid-level (around CA$128,400) to Staff ML Engineer / Principal AI Engineer level typically adds 30–50% to base salary, pushing total compensation well above CA$241,520. The increase isn't just tenure — it reflects expanded scope, ownership of systems, and the ability to operate without close direction. Companies at the Staff ML Engineer / Principal AI Engineer level also tend to be more flexible on equity and signing bonuses.