Machine Learning Engineer

San Francisco โ€ข $130k - $190k โ€ข 0.25% - 1.25%

Cushion AI, Inc.

Role Location

  • San Francisco


  • $130k - $190k
  • 0.25% - 1.25%


< 10 people


845 Market St
San Francisco, CA, 94103-1923, US

Tech Stack

  • Python
  • Django
  • AWS
  • MySQL
  • React
  • Node.js

Role Description

Cushion is looking for a stellar Machine Learning Engineer to join us during this exciting phase of the company!

Weโ€™re growing, generating revenue, and announced our $2.8M Seed round on TechCrunch in 2019. In addition, we have been recognized by SXSW, Bloomberg, American Banker, Inc magazine, and more.

This is a rare opportunity to join a startup as one of the first 10 employees and shape the product, strategy, and culture alongside the Founder and core team.

Who we're looking for

The core of what we're building at Cushion is a system that can perform intelligent financial actions on behalf of a consumer, better than they can. This could be things like making off-cycle credit card payment on behalf of someone to improve their credit score or predicting a potential overdraft fee and moving money around to avoid it.

We are on the hunt to find a humble hard-working ML Engineer who is an outstanding engineer first and foremost (e.g. can build and deploy a web app from scratch if need be). This person must be able to not only extract insights from data and build ML models, but is also able to deploy their models into production without the help of other engineers.

The ideal candidate is curious, driven, absolutely loves solving complex problems, is a pleasure to be around and work with, and has an intense bias towards making stuff happen.

As an engineer at Cushion, you will:

  • โœ‹ have serious ownership - of the work that you do as well as your stake in the company
  • ๐Ÿƒโ€โ™‚๏ธ work in a fast-paced environment where an idea on Monday can become a live feature in the hands of users by Friday
  • ๐Ÿ‘ฉโ€๐Ÿ’ป work on high-impact initiatives that will affect tens of thousands of customers (hopefully millions as we grow!)
  • ๐Ÿš€ be a major contributor in building and scaling a company

As a Machine Learning Engineer at Cushion, you will build and deploy models that do things like:

  • ๐Ÿ”ข Evaluate different scenarios for a consumer based on their financial transactions and balances
  • ๐Ÿ”ฎ Predict when a person might overdraft their account (or get hit with some other type of fee) and help them avoid it
  • ๐Ÿ“‰ Identify opportunities to reduce financial waste
  • ๐Ÿ’ฐ Programatically help the consumer build a nest egg while making sure they can still afford to pay their bills
  • ๐Ÿ’ฌ Communicate (read/write) intelligently (with banks, utility companies, etc. ) on behalf of the end-customer

What we're looking for

Based on our experience building teams at multiple companies, including Twitter, we're looking for candidates with the following background:

  • A college degree in Computer Science, Computer Engineering, Math, or Physics
  • At least 4 years of full-time Software Engineering experience after getting your undergraduate degree
  • At least 2 years of Machine Learning experience
  • A track record of deploying ML models into production yourself
  • Experience with AI, NLP, ML
  • Experience with Python
  • Experience with relational databases and SQL
  • Experience deploying applications on AWS, Google Cloud, Azure, etc
  • Bonus: Prior startup experience
  • Bonus: Master's Degree or higher in Machine Learning

About Cushion AI, Inc.

At Cushion, our goal is to democratize access to financial help, not just financial advice - enabling consumers to waste less money, save more, and live financially healthier lives.

Our first service is a bot that negotiates with banks, on behalf of our customers, to get back money wasted on bank fees & credit card interest โ€” a $200 Billion problem in the U.S. each year with no other digital solution until now.

Company Culture

We value a scrappy, resourceful, problem-solving attitude towards work. We're a small team trying to accomplish big things and help millions of people in the process. We spend a lot of hours together and are all mission aligned to push the company forward every day. We also have frequent happy hours to blow off some steam!

Interested in this role?
Skip straight to final-round interviews by applying through Triplebyte.

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