Machine Learning salaries in Toronto.
What Machine Learning roles in Toronto pay, from live listings on JobsRadar.
Compare with anotherMedian salary
$135,918
per year · annualized USD
Typical range
$103.4k – $178k
25th–75th percentile
Disclosing pay
27.4%
158 of 577 roles
Live roles
577
open right now
Salary trend
median · annualized USDSalary distribution
annualized USD · disclosed rolesHighest-paying jobs
Director, ML Engineering & Infrastructure
Software Engineer, ML Infra & Distributed Systems (Staff & Principal)
Principal Forward Deployed Engineer - Okta for AI Agents
Machine Learning Engineer (Staff & Principal)
Senior Manager, Site Reliability Engineering
Machine Learning Engineer, Detection (TOR)
Enterprise Account Executive (Auth0)
Member of Technical Staff - System Engineering
Top companies hiring
| Company | Median | Roles |
|---|---|---|
|
Okta
|
$135,918 | 42 |
Geotab
|
$85,218 | 17 |
Hopper
|
$180,089 | 9 |
Serve Robotics
|
$242,500 | 7 |
Robinhood
|
$203,500 | 7 |
HelloFresh
|
$121,167 | 6 |
Snowflake
|
$109,945 | 5 |
|
Tubi
|
$306,300 | 4 |
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How much do Machine Learning roles in Toronto pay?
The median salary for Machine Learning roles in Toronto is $135,918 per year. Most pay falls between $103,376 (25th percentile) and $177,995 (75th percentile), with the broader 10th–90th percentile band running from $81,212 to $234,075.
These figures are computed live from 577 active Machine Learning roles in Toronto on JobsRadar, of which 158 (27.4%) publish a salary range. Pay is normalized to annualized USD so roles can be compared on equal terms; the highest-paying roles listed above show their original posted currency. Numbers refresh every few hours as new roles are posted and older ones close.
Employers currently hiring well-paid Machine Learning roles in Toronto include Tubi, Okta, Doppel, Phylo and Inc..
Salary transparency varies by employer and region, so the disclosing share above reflects only roles that publish pay — not every open position. Use it as a directional benchmark rather than an exact offer.