Posting record
Open 17+ days
- Bree's site dates the posting
- Ghostless first sees this listing
- Last checked: still up
How we know
It hasn't been reposted, listed twice, or left up unusually long, and the posting doesn't say it's a talent pool.
Ghostless records the day it first sees a posting, so a repost can't reset its age. This one was already up when Ghostless started tracking Bree, so its true age is longer.
Last checked Nov 3, 2026.
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Upload your resumeWhat it asks of you
- Must be a current student
What the posting discloses
- Pay
- $50 to $70 an hour CAD
Compensation: $50-$70/hour, based on experience and interview performance (quoted from the posting)
Not stated: Real vacancy, AI screening.
Why these three
Ontario requires postings from employers with 25 or more staff to state the pay, whether the vacancy exists, and whether AI screens applicants.
Skills mentioned
About the role
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
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