Machine Learning Engineer

4 weeks ago

Toronto, Canada Bree Technologies (YC S21) Full time

Overview:

Bree is a financial technology company creating best-in-class lending products for consumers and businesses.
Our consumer business serves everyday Canadians overlooked or underserved by legacy financial institutions. We are building a suite of financial products that is friendlier, more intuitive, more helpful and lower-cost than existing solutions, empowering our customers and improving their financial health. Our flagship product is an interest-free line of credit that provides short-term liquidity to our customers with no hidden fees.
Over the next 5 years, our vision is two fold:

To build a highly profitable Swiss Army Knife of consumer fintech products which acquires customers via lending products—enabled by building at the leading edge of lending technology.
Provide legacy lenders, fintech startups and embedded lenders with state-of-the-art lending orchestration software—the same tools that have been battle-tested on our platform. We are building differentiated software by eating our own cooking.

Founded in 2021, Bree has raised more than $2 million in funding from world-class technology investors including Y Combinator, Global Founders Capital, and other top-tier angel investors including executives and founders of Meta (Facebook) and Forge Global. We are fortunate to have a very healthy core business with tremendous runway having grown 10x in the last year to 7 figures of annualized revenue, with an expectation to break 8-figures by the end of the year. Bree is headquartered in Vancouver, B.C. and we are excited to continue bringing world-class talent onboard to help shape the next chapter of our growth.

The role:

We are seeking a Machine Learning Engineer who will play a pivotal role in enhancing our credit decisioning processes through the development and deployment of advanced machine learning models. This role involves both refining existing models and innovating new solutions that will drive all aspects of data-related decision making across the company.

What you'll do:

Develop and Deploy Machine Learning Models : Design, build, and integrate machine learning models into the existing underwriting system to enhance decision-making and risk assessment capabilities. Ensure models are scalable, maintainable, and can be updated easily as new data becomes available.
Machine Learning Operations (MLOps) : Establish and maintain MLOps practices to streamline model development, testing, deployment, and monitoring. Implement continuous integration and deployment (CI/CD) pipelines for machine learning systems to improve model reliability and performance in production.
Performance Monitoring : Monitor the performance of machine learning models in production to ensure they maintain high accuracy and efficiency. Adjust and recalibrate models as necessary based on performance data and changing market conditions.
Collaboration with Engineering Teams : Work closely with software engineering team to integrate ML models seamlessly into the existing infrastructure and data pipelines. This includes optimizing data flow and storage to support model inputs and outputs efficiently.

Why you should join us:

This is a great role for an exceptional ML engineer that is interested in working at an early-stage, high-growth startup and play a pivotal role.

We are at an extremely exciting stage as a company. We’ve built a product that has proven demand, raised capital from world class investors, and are looking to build the core team to scale our business beyond profitability. You will be on the ground floor of an early-stage company as we hyper-scale from mid 7 figures of annualized revenue to 8 figures and beyond over the next year.

Who you are:

You bring at least 3 years of professional experience in data science or machine learning, with a proven track record of deploying scalable and effective models, ideally in high-stakes environments like financial services.
You possess a strong intuition for leveraging data to address business challenges, backed by a robust skill set in data mining, statistics, and mathematical modeling.
You are highly proficient in programming languages used in data science, such as Python or R, and have extensive experience with machine learning libraries and frameworks
You are constantly on the lookout for emerging trends and technologies in machine learning and data science. You proactively seek out new data sources and analytical techniques to improve model accuracy and performance.
Entrepreneurial spirit, comfortable with ambiguity and complexity, and efficient in managing limited resources.
Low ego, extremely intelligent, quick to learn, and willing to roll up your sleeves to tackle tasks - big or small.

Bonus:

Prior experience in fintech.
Based in Vancouver.

Perks:

Generous equity package.
Ownership and responsibility.
Unlimited vacation.
Benefits package (dental, etc.) + $1,000 annual wellness benefit on anything you want.

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