Tech Lead Manager - Machine Learning at Square

San Francisco
a year ago

Company Description

Cash App is the fastest growing financial brand in the world. Built to take the pain out of peer-to-peer payments, Cash App has gone from a simple product with a single purpose to a dynamic money app with over 36 million active monthly users. 

Loved by customers and by pop culture, we’ve held the #1 spot in finance on the App Store for almost two years, and our social media posts see more engagement in a day than most financial brands see in a year. 

With major offices in San Francisco, New York, St. Louis, Portland, Kitchener-Waterloo, Toronto and Melbourne, Cash App is bringing a better way to send, spend, and save to anyone who has ever sought an alternative to today’s banking system.

Job Description

We are hiring a Machine Learning (ML) Engineering Tech Lead Manager to build and lead Cash App's MLE Lending team. This role reports directly to the Head of Applied ML and will involve building our MLE Lending team from scratch. It will be your team's core responsibility to build, maintain, and evolve the infrastructure and tooling that powers our ML applications in production, at scale. In doing so, you will partner frequently with our ML Modeling and platform-focused ML teams.

You will:

  • Build and grow the MLE Lending team
  • Take an active role in defining our MLE discipline and recruiting senior ML Engineers, with diversity being top of mind
  • Design and build new ML systems, services, and models that have a large impact on both our customers and our business
  • Lead complex technical, architecture, design, and product discussions
  • Provide coaching and mentorship to Engineers within your team and across the organization
  • Foster a culture of ownership, inclusiveness and urgency in the team
  • Hold your teammates - and yourself - to high engineering standards


You have:

  • 7+ years of software development/machine learning experience
  • 1+ years experience managing or mentoring engineers, including providing technical guidance and helping team members grow
  • Experience creating readable, well-crafted, maintainable code
  • Knowledge of the most advanced and up-to-date ML platforms and frameworks
  • Eagerness to share your ideas, and openness to those of others

Some technologies we use and teach:

  • Java 11 including JUnit, Hibernate, Guice, and Jersey
  • Kotlin and Python
  • MySQL
  • gRPC and Protocol Buffers
  • Amazon Web Services & Google Cloud Platform
  • Kafka, Flink, and Segment
  • Event-driven architecture

Additional Information

We’re working to build a more inclusive economy where our customers have equal access to opportunity, and we strive to live by these same values in building our workplace. Square is a proud equal opportunity employer. We work hard to evaluate all employees and job applicants consistently, without regard to race, color, religion, gender, national origin, age, disability, veteran status, pregnancy, gender expression or identity, sexual orientation, citizenship, or any other legally protected class. 

We believe in being fair, and are committed to an inclusive interview experience, including providing reasonable accommodations to disabled applicants throughout the recruitment process. We encourage applicants to share any needed accommodations with their recruiter, who will treat these requests as confidentially as possible.

Additionally, we consider qualified applicants with criminal histories for employment on our team, assessing candidates in a manner consistent with the requirements of the San Francisco Fair Chance Ordinance.

Square, Inc. (NYSE: SQ) builds tools to empower businesses and individuals to participate in the economy. Sellers use Square to reach buyers online and in person, manage their business, and access financing. Individuals use Cash App to spend, send, store, and invest money. And TIDAL is a global music and entertainment platform that expands Square's purpose of economic empowerment to artists. Square, Inc. has offices in the United States, Canada, Japan, Australia, Ireland, Spain, Norway, and the UK.

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