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Machine Learning Engineer


Headquarters: San Francisco, CA
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Chime is dedicated to helping our members lead healthy financial lives. That’s why we offer an award-winning bank account that doesn’t charge unnecessary fees, gives members early access to their paychecks, and helps them save money automatically. Hundreds of thousands of people use the Chime mobile app and debit card to make purchases, track spending, save for the future, and more. Our members love Chime and use it daily.

We believe the big banks fail to help their members achieve financial health - and in many cases work against it, charging hundreds of dollars in hidden fees and pushing products that drive people into debt. We don’t think it needs to be this way, so we’re out to beat them.

We have one of the most experienced management teams in Fintech. We have raised over $100M in funding are backed by Menlo Ventures, Omidyar, Crosslink, and others. If you’re looking to join a small but fast-growing company with a beloved, daily-use product and an authentic mission that puts people first, we want to meet you.

Chime is a technology and data-driven consumer bank. We are amassing vast amounts of data that we want to use to ensure we’re the best in risk management, new user acceptance, information security, underwriting, and more. Our ML and Data Science team occupy a critical role in the company, creating models and infrastructure that allow us to evaluate events in realtime in new, efficient, and accurate ways so as to minimize fraud and scale our ability to manage risk.

What You’ll Do

In this role, you’ll build and implement novel Machine Learning and Deep Learning systems to combat fraud on our platform as well as help build the infrastructure to train and deploy them.   Specifically, you’ll:

  • Design and implement the infrastructure required to train models at scale. Okay to leverage AWS Sagemaker and other such tools initially

  • Implement ML/DL models that fight fraud and minimize the company’s risk

  • Work with the data team’s infrastructure to build real-time and offline feature databases

  • Help build the model serving systems with which we can deploy our models to production

  • As we grow, scale the ML system to be able to support more use cases and ML model types

Qualifications & Requirements
  • One of the following: (a) MS in CS or related field with 1+ years of experience in implementing and deploying large scale ML solutions OR (b) Ph.D. in Machine Learning, Statistics, Optimization, Physics, or related field, with 1+ years experience building production-ready ML models and systems

  • Strong software engineering fundamentals - understanding of data structures and algorithms, O-notation, ability to maintain a test suite and write clear maintainable code

  • Familiarity with a majority of the following tools: Tensorflow, Numpy, Scipy, SparkML, pandas, scikit-learn, Hadoop, Spark, Hbase, Cassandra etc.

  • Strong programming skills in Python. Intermediate to advanced knowledge of SQL and ability to wrangle data from many disparate data sources

  • Technologies we use: MySQL, Python, AWS, Snowflake, R, and Looker, among many others

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. Chime is proud to be an equal opportunity employer.

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