Machine Learning Engineer, Ecommerce

  • San Francisco, CA
  • Full-time

Company Description

Weebly was acquired by Square in May 2018. Founded in 2007, Weebly is a complete platform that allows anyone to start and grow an online business with curated website templates, powerful e-commerce and integrated marketing. More than 40 million entrepreneurs around the world use Weebly to grow their customer base, fuel sales and market their idea. Designed for any entrepreneur who wants to reach a global audience, Weebly gives everyone the freedom to create a high ­quality site and store that works brilliantly across any device. Weebly offers a range of pricing options, including free and premium consumer plans, as well as enterprise offerings and is consistently the highest rated website building mobile app in the App Store and Google Play.

Job Description

ML engineers on the Square Ecommerce team have deep expertise in software engineering, data engineering, machine learning, and in general, building cool stuff. We process data about hundreds of millions of monthly users on our ecommerce platform to build prediction algorithms for user behavior in product, conversion rate, marketing strategies, product recommendations etc. We use a mix of open source and home grown tools in a hybrid on-premise and cloud environment to do data magic.


As an ML engineer on the Square ECOM team, you will:

  • Build, train and deploy machine and deep learning models and systems that operate effectively at scale and are used to understand key customer behaviors, surface product recommendations, automatically infer responses to inbound customer inquiries, detect fraud/spam, and overall make our products and services even better for our customers.
  • Work alongside product teams to design and build user facing features involving machine learning.

  • Work alongside data engineering to ingest and transform data for both streaming and batch machine learning applications.

  • Collaborate with decision makers and subject matter experts to first understand the problems as well as share and contextualize the findings.

  • Creatively leverage both new and existing data to increase the effectiveness and efficiency of our risk infrastructure.

  • Apply good software development practices and actively contribute to production code.

  • Help build the next generation of data products at Square


You have battle scars to show for these:

  • 2-4 years of relevant industry experience.

  • A graduate degree in statistics, applied mathematics, computer science, physical sciences, or a similar technical field.

  • Experience developing and deploying machine learning & deep learning solutions.

  • The versatility to communicate clearly with both technical and non-technical audiences.

  • A willingness to solve problems using whichever tool is most appropriate for the situation.

  • Technologies we use: Python, Spark, Docker, MySQL, Snowflake, PHP, AWS, GCP, Looker

Additional Information

At Square, our purpose is to empower – within and outside of our walls. In order to build the best tools for the businesses and customers we support all over the world, we have to start at home with a workforce as diverse and empowered as our sellers. To this end, we take great care to evaluate all employees and job applicants equally, based on merit, competence, and qualifications. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, disability status, or any other characteristic protected by law. We encourage candidates from all backgrounds to apply and always consider qualified applicants with arrest and conviction records, in accordance with the San Francisco Fair Chance Ordinance. Applicants in need of special assistance or accommodation during the interview process or in accessing our website may contact us by sending an email to assistance(at) We will treat your request as confidentially as possible. In your email, please include your name and preferred method of contact, and we will respond as soon as possible.