Machine Learning Engineer, Cash
- San Francisco, CA, USA
We are looking for machine learning engineers to join Square and help build Cash App, the fastest growing financial app in the world. Our mission is to make banking and financial services accessible to the underserved and unbanked. We move quickly, make incremental changes, and deploy to production every day.
As a machine learning engineer at Square, you will work alongside product engineering teams and data scientists to unlock the potential in our large and unique data by building machine learning systems that are used to detect fraud, automatically infer responses to inbound customer inquiries, understand key customer behaviors, surface product recommendations, and much more. You will also contribute directly to training machine learning models using techniques such as gradient boosted trees and deep learning.
- Design and build systems to ingest and transform data for machine learning applications for our rapidly growing customer base
- Collaborate with data scientists to train machine learning models using state-of-the-at techniques
- Collaborate with subject matter experts and decision makers on how to design for and apply machine learning techniques in practice
- Evangelize machine learning within product engineering teams
- Help build the next generation of data products in Cash App
- 3-5 years of relevant industry experience
- A graduate degree in software engineering, computer science, machine learning, artificial intelligence, applied mathematics, statistics, or a similar technical field.
- Experience applying statistics and machine learning to creatively solve complex business problems
- An appreciation for the connection between the software you build and the experience it delivers to customers
- Technical initiative and a desire to perform and grow as an engineer and scientist
Technologies we use and teach
- Java 9 including JUnit, Hibernate, Guice, and Jersey
- Python (numpy, pandas, sklearn, xgboost, TensorFlow, etc.)
- MySQL, GCP, AWS
At Square, we value diversity and always treat all employees and job applicants based on merit, qualifications, competence, and talent. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. We will consider for employment qualified applicants with criminal histories in a manner consistent with the requirements of the San Francisco Fair Chance Ordinance.