We've opened an office in Poland with a goal to hire a substantial team of talented engineers within the first year. Read more about our plans here.

The Shopping Core ML team’s mission is to deliver state of the art ML algorithms that will help build robust and scalable customer products. We use a data-driven approach to solve the problems and deliver ML-powered smart user experiences on the consumer apps and website. This team works in close partnership with our product managers, application and website teams to deeply understand the problems and deliver the most impactful solutions. We are constantly faced with challenges at industrial scale such as Personalization, Information Retrieval, Relevance Ranking and are pushing the boundary of how Affirm thinks of its data.

We are looking for highly motivated senior engineers to help build this team in Poland. Come join us!

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
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What We Look For

• B.S. with 2-3 years of industry experience, M.S. with 1-2 years, 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