Machine Learning Engineering, Intern
BreeAdded 1mo ago
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Quick summaryby newgrad.ai
What you'll do
- Prepare and validate datasets used in modeling and analysis pipelines
- Contribute to developing and assessing models for credit assessment, fraud prevention, and user engagement
- Create automation and testing infrastructure to streamline the experimentation process
- Understand how trained models perform once deployed, monitoring for quality issues and performance degradation
What they're looking for
- Pursuing a degree in Computer Science, Statistics, Engineering, Data Science, or equivalent field
- Proficient in Python with hands-on data work from classes or personal projects
- Basic grasp of statistical and machine learning principles demonstrated through academics or projects
- Familiarity with frameworks like PyTorch, LightGBM, or contemporary language model approaches preferred
Pay and perks
- $50-$70/hour depending on background and interview results
- $250 monthly food allowance and twice-yearly team gatherings
- 8-month internship with dedicated mentoring and professional development sessions
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
From Bree's public posting, laid out for reading by newgrad.ai with the wording unchanged. Check the original before you apply.
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