Time since we first saw it
Day 119
Up longer than most. Similar jobs usually come down between day 8 and day 76.
From 5,516 similar postings that came down. Coming down is not always a hire.
Machine Learning Engineering, Intern
Toronto · Toronto, ON, Canada
Open 3 months, first seen by us 119 days ago- Pay
$50–70/hour — pay source
Benefits Compensation: $50-$70/hour, based on experience and interview performance Offer Matching: We're open to matching competing offers
Read the full posting- Work setting
Hybrid — work setting source
Location type: Hybrid
From the employer’s posting- Employment
Internship — employment source
Employment type: Internship
From the employer’s posting- Team
Internship & Co-ops — team source
Department: Internship & Co-ops
From the employer’s posting
Before you apply
- New graduates
- For current students
Job title: Machine Learning Engineering, Intern
What you’ll work on
Full postingWe’re looking for a Machine Learning Engineering Intern to work alongside our ML, data, and infrastructure teams.
At Bree, co-ops are full members of the Engineering team.
Prepare, explore, and validate data used in models and analytics
Support training and evaluation of credit risk, fraud, and customer experience models
Build scripts, tools, and tests to make model evaluation repeatable
Learn how production models are monitored for drift and data quality
Document results, tradeoffs, and next steps from explored approaches
From the employer’s posting
We’re looking for a Machine Learning Engineering Intern to work alongside our ML, data, and infrastructure teams. You’ll contribute to real modelling and data problems, learn how production ML systems are evaluated and monitored, and use AI tools thoughtfully to move from experimentation to reliable implementation.
At Bree, co-ops are full members of the Engineering team. You’ll work on the same customer and business problems as full-time engineers, ship real production work, and take part in design discussions, code reviews, testing, and releases. We pair that responsibility with close mentorship, clear context, and projects scoped for you to make a meaningful impact from day one.
Help prepare, explore, and validate data used in models and analytical workflows.
Support training and evaluation of models used for areas such as credit risk, fraud detection, and customer experience.
Build scripts, tools, and tests that make experimentation and model evaluation more repeatable.
Learn how model performance is monitored in production, including data quality, drift, and operational reliability.
clearly document results, tradeoffs, and next steps.
What you’ll bring
All qualificationsCore experience
- Strong Python foundations, plus experience working with data through coursework or projects.
- Familiarity with SQL, pandas, or similar tools is helpful.
Qualification wording
Strong Python foundations, plus experience working with data through coursework or projects. Familiarity with SQL, pandas, or similar tools is helpful.
About Bree
Bree is a consumer finance platform that brings better, faster, and cheaper financial services to over half the Canadian population who live paycheck to paycheck.
In the employer’s words · Read in context · Company website ↗
Posting record
Report an errorOpen 3 monthsWe first saw this posting 119 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
- Status in our records
- Live
- First seen by us
- Jul 18, 2026119 days ago
- Recorded sightings
- 66
- Last seen by us
- Nov 14, 2026
- Employer says posted
- Jul 15, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Bree is hiring
3 open jobs
- No new data jobs since July
See how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Python
- SQL
- LightGBM
- pandas
- PyTorch
Where the posting names them
- Currently enrolled in a Computer Science, Statistics, Engineering, Data Science, or related post-secondary programme, and available for the full 8-month term. - Strong Python foundations, plus experience working with data through coursework or projects. Familiarity with SQL, pandas, or similar tools is helpful. - Foundational knowledge of statistics and machine learning concepts, with coursework, research, personal projects, or competitions you can discuss.
- Foundational knowledge of statistics and machine learning concepts, with coursework, research, personal projects, or competitions you can discuss. - Interest in tools such as PyTorch, LightGBM, or modern LLM workflows. Production ML experience is not required. - Curiosity, rigour, and strong communication. You enjoy investigating ambiguous problems, checking your assumptions, and learning from feedback.
Your next step
Complete your application on jobs.ashbyhq.com. The employer’s form will show what is required.
Applying through Ashby
- No account needed. “Autofill from resume” at the top of the form fills the key fields from your file.
Already applied? Track this application
Demand for ML Engineer roles
New ML Engineer postings at the employers we follow are up 10% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
About the role
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
US government figures for computer and information research scientists
- Median yearly pay, May 2025
- $140,300
- Expected change, 2025 to 2035
- 21.8% more jobsagainst 3.5% for all jobs
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
Job description
About Bree
Bree is a consumer finance platform that brings better, faster, and cheaper financial services to over half the Canadian population who live paycheck to paycheck. We operate in a huge, but overlooked market in a country with the least amount of financial technology innovation in the developed world. Our first act is to become the cheapest and best provider of short-term credit to the 20 million people in Canada who live paycheck to paycheck.
More than 800,000 Canadians have already signed up with Bree and we believe we are just scratching the surface. We are in an exciting place where we have product market fit, explosive growth, and a clear path to becoming one of the most important FinTechs in Canada.
About the Role
We’re looking for a Machine Learning Engineering Intern to work alongside our ML, data, and infrastructure teams. You’ll contribute to real modelling and data problems, learn how production ML systems are evaluated and monitored, and use AI tools thoughtfully to move from experimentation to reliable implementation.
This is an 8-month co-op term.
At Bree, co-ops are full members of the Engineering team. You’ll work on the same customer and business problems as full-time engineers, ship real production work, and take part in design discussions, code reviews, testing, and releases. We pair that responsibility with close mentorship, clear context, and projects scoped for you to make a meaningful impact from day one.
What You'll Do
Help prepare, explore, and validate data used in models and analytical workflows.
Support training and evaluation of models used for areas such as credit risk, fraud detection, and customer experience.
Build scripts, tools, and tests that make experimentation and model evaluation more repeatable.
Learn how model performance is monitored in production, including data quality, drift, and operational reliability.
Explore new approaches with mentorship, then clearly document results, tradeoffs, and next steps.
What You'll Need
Currently enrolled in a Computer Science, Statistics, Engineering, Data Science, or related post-secondary programme, and available for the full 8-month term.
Strong Python foundations, plus experience working with data through coursework or projects. Familiarity with SQL, pandas, or similar tools is helpful.
Foundational knowledge of statistics and machine learning concepts, with coursework, research, personal projects, or competitions you can discuss.
Interest in tools such as PyTorch, LightGBM, or modern LLM workflows. Production ML experience is not required.
Curiosity, rigour, and strong communication. You enjoy investigating ambiguous problems, checking your assumptions, and learning from feedback.
Benefits
Compensation: $50-$70/hour, based on experience and interview performance
Offer Matching: We're open to matching competing offers
Perks: $250 monthly lunch stipend, bi-annual company retreat
Impact: Push to prod, with 10x the ownership and impact of typical roles
Growth: Mentorship programs and career training sessions
Path to Full-Time: Strong conversion opportunities for high performers
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
Benefits Compensation: $50-$70/hour, based on experience and interview performance Offer Matching: We're open to matching competing offers
- Location & working pattern
Toronto, ON, Canada
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.