Software Engineer, Machine Learning
Remote Canada
Affirm
With Affirm, you can pay over time at your favorite brands. No late fees or compounding interest—just a more responsible way to say yes to the things you love.Affirm is reinventing credit to make it more honest and friendly, giving consumers the flexibility to buy now and pay later without any hidden fees or compounding interest.
Machine learning is a critical tool in this effort! As a member of the software engineering team, you will design, build, optimize, and support machine learning systems both offline and real time. You will also have the opportunity to partner with Data Science and product teams across Affirm, leveraging your machine learning and software development skills to solve challenging problems that will improve the financial lives of millions of people.
What you'll do
- Partner with Data Science and Product engineering teams to build production machine learning models; your models will decide who we lend to in real time, and how we interact with our existing customers
- Develop the core decisioning service supporting our machine learning models in production
- Optimize the decisioning service with respect to the accuracy of the underlying models, the latency of different 3rd party data sources, and the expected financial cost of those data sources
- Develop our understanding of new data sources and how they may improve our existing processes
- Design, develop, and deploy infrastructure for the training, testing, and serving of models at scale
- Work closely with Affirm’s credit, risk, and analytics teams to understand our risk modeling strategy and the business drivers underlying that strategy
What we look for
- B.S. with 2+ years of industry experience, M.S. with 1+ year, or PhD
- Deep understanding and experience with data engineering, data analysis, and statistical modeling, in the development of real-time services
- Proficiency writing production-quality software following software engineering best practices, preferably industry engineering experience with machine learning projects (e.g. recommendation, ranking, optimization)
- Strong foundation in machine learning with experience implementing and optimizing machine learning models
- Hands on experience with Python, Spark, XGBoost, Airflow, and AWS (EC2, EMR, etc.) a plus
- Ability to work efficiently both solo and as part of a team; willingness to learn new things
- Passion and drive to change consumer banking for the better, while developing a deeper understanding of applied machine learning
Tags: Airflow AWS Banking Data analysis EC2 Engineering Machine Learning ML models PhD Python Spark Statistical modeling Testing XGBoost
Perks/benefits: Career development Team events
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