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. Affirm proudly includes Returnly.
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- Design, develop, and deploy a ML-powered solution for building effective personalized user experiences, search optimization and other challenging problems in customer space
- Build tools for our team to enable (1) personalization of content (2) relevance ranking, and (3) better and more effective information retrieval
- Partner with Analyst, Data Science, and Product engineering teams to build production machine learning models; your models will decide what, when and to who will be shown in our app and website
- Develop our understanding of new data sources and how they may improve our existing processes
- Work closely with Affirm’s mobile application, website application, marketing, and analytics teams to understand our performance modeling strategies and the business drivers underlying those strategies
- Serve as a trusted advisor on the application and implementation of machine learning across Affirm.
- B.S. with 8+ years of industry experience, M.S. with 7+ years, PhD with 6+ years, or equivalent experience
- Demonstrated experience designing real time systems and writing production-quality software
- Experience with the AWS technical stack and data infrastructure such as MySQL, Spark, Kubernetes, Docker, and Airflow
- Proficiency in machine learning with experience in areas such as gradient boosting, deep learning, recommendation systems, computational advertising, reinforcement learning, financial forecasting, time series analysis, anomaly detection, monte-carlo simulations, and Markov decision processes
- Strong programming skills in Python. Experience using frameworks for machine learning and data science like scikit-learn, pandas, numpy, XGBoost, TensorFlow, mllib
- Excellent written and oral communication skills including the capability to drive requirements with product and engineering teams and present technical concepts and results in an audience-appropriate way
- Ability to work efficiently both solo and as part of a team; willingness to learn new things and mentor others
- Passion to change consumer banking for the better, while developing a deeper understanding of applied machine learning.
We offer a competitive package, with some highlights listed below. However, the given figures are not guaranteed compensation ranges; rather, they are unbinding, approximate indications of what the salary may be for your awareness. The actual salary may be less than the lower range or greater than the upper range, depending on skills and experience. No employee is guaranteed salary at the amount of the lower range.
- Targeted Gross Monthly Salary: 25,792 - 32,233 PLN
- Flexible Spending Wallets for tech, food and lifestyle
- Generous time off policies
- Away Days - wellness days to take off work and recharge
- Learning & Development programs
- Parental leave
- Robust health benefits
- Employee Resource & Community Groups
Location - Remote Poland
The majority of our roles can be located anywhere in Poland.
Affirm is proud to be a remote-first company! The majority of our roles are remote and can be located anywhere in the U.S. and Canada (with the exception of the U.S. Territories, Quebec, Yukon, Nunavut, and the Northwest Territories) unless the job indicates a different global location. We are currently building operations in Spain, Poland, and Australia. Employees in remote roles have the option of working remotely or from an Affirm office in their country of hire, and may occasionally travel to an Affirm office or elsewhere for required meetings or team-building events. Our offices in Chicago, New York, Pittsburgh, Salt Lake City, San Francisco and Toronto will remain operational and accessible for anyone to use on a voluntary basis, subject to local COVID-19 guidelines.
[For U.S. Candidates] All full-time jobs at Affirm (excluding interns and apprentices) are tied to a transparent grade-based pay range taking location into account. The grade for this position is noted above and in accordance with various U.S. pay transparency laws, we provide the base pay range and benefits for our U.S.-based positions in the links below:
At Affirm, People Come First is one of our core values, and that’s why diversity and inclusion are vital to our priorities as an equal opportunity employer. You can read about our D&I program here and our progress thus far in our 2021 DEI Report.
We also believe It’s On Us to provide an inclusive interview experience for all, including people with disabilities. We are happy to provide reasonable accommodations to candidates in need of individualized support during the hiring process.
By clicking Submit Application, you acknowledge that you have read the Affirm Employment Privacy Policy for applicants within the United States, the Affirm Employment Privacy Notice (EU) for applicants applying from the European Union, or the Affirm U.K. Limited Employee Notice Regarding Use of Personal Data for applicants applying from the United Kingdom, and hereby freely and unambiguously give informed consent to the collection, processing, use, and storage of your personal information as described therein.
