Machine Learning Engineer at Kabbage
Atlanta, GA, US / New York City, NY, US / San Francisco, CA, US

Kabbage is setting a new standard in big data and FinTech, and we are looking for a Machine Learning Engineer to join us as we continue our amazing growth trajectory. As we offer the only fully automated, online lending platform designed to support continuous customer data monitoring, Data Science is one of the pillars of Kabbage's persistent innovation and sets the standard for automated lending.

Kabbage is more than a lender for small businesses; our data and technology platform is now being used as a fully branded product by other lenders, and our products are growing rapidly. We've received numerous awards and recognition, including Glassdoor's 2017 Best Places to Work, "36th fastest growing company in the US" on the INC 500 List, Fast Company's "Top 10 most innovative companies in finance" and Forbes' "America's Top 100 Most Promising Companies" among others.

Your mission:

Developing a model is just part of data science. We want to democratize who has access to those tools, and we want to train, run, and deploy those models as quickly as possible. Your mission is to automate the data science pipeline and create the infrastructure to turn out models quickly and reliably, which in turn will help small-to-medium sized businesses thrive.

What you'll be doing:

  1. Create the infrastructure to quickly develop models and deploy them.
  2. Create the tools to help non-data scientists develop insights into their data.
  3. Manage and automate Kabbage's data pipeline, including the introduction of new data sources and improving the speed of existing pipelines for ingesting and transforming data.
  4. Work across teams and determine how to solve problems with others, including management, engineers, and data scientists.
  5. Communicate data science concepts and findings clearly to technical and non-technical audiences. Understand the needs of both data scientists and engineers.

What we're looking for in you:

  • Intelligence: Learns quickly. Demonstrates ability to quickly and proficiently understand. You have an aptitude to independently learn new technologies.
  • Analytical Skills: Able to structure and process qualitative or quantitative data and draw insightful conclusions from it; exhibits a probing mind and achieves penetrating insights.
  • High Standards: Expects personal performance and team performance to be nothing short of the best.
  • Teamwork: Reaches out to peers and cooperates with supervisors to establish an overall collaborative working relationship.
  • Creativity: Able to think about traditional questions in a creative way to find new solutions given new data or circumstances.
  • Proactivity: Acts without being told what to do. Brings new ideas to the company.
  • Communication: Excellent written and oral communication skills and ability to share findings with a large, non-technical audience.
  • Attention to Detail: Does not let important details slip through the cracks or derail a project. You're a perfectionist who tempers perfection with deadlines.
  • Persistence: Demonstrates tenacity and willingness to go the distance to get something done.

What you should have:

  • Worked with distributed and parallel systems.
  • Worked with a couple of different data storage technologies (e.g., RDBMS, key-value, object stores, columnar stores, document stores, streams, or high-performance storage), and you know their strengths and weaknesses.
  • Know how to monitor and optimize systems, and you also know how to optimize the code and how it’s designed.
  • Familiar with containers, virtual machines, and orchestration tools.
  • Systems fundamentals, including concepts such as consistency and concurrency.
  • Can write code in Python (preferred) or R, and you’re comfortable with other procedural languages like Java, Scala, C, or C++.
  • Familiarity with modeling tools and libraries such as scikit-learn, xgboost, pandas, or Caret.

Bonus points:

  • You have a master's degree or PhD in a related field.
  • You've used visualization tools such as StreamSets or Tableau.
  • You're familiar with deep learning tools and frameworks such as Keras, PyTorch, Caffe, and TensorFlow.
  • You have a background in probability or advanced math.

The Kabbage Advantage

At Kabbage, our people are awesome, so we built the Kabbage Advantage—our way of being awesome right back. We offer competitive benefits including unlimited PTO, equity in the company, and exceptional health coverage options. Our team members enjoy a dynamic work environment with daily catered lunches, fully stocked kitchens, and onsite fitness classes.

While our perks and benefits are generous, the people are actually what make Kabbage great. Kabbagers are curious, creative, and resilient. We are enthusiastic, productive, and problem solvers. And we don’t do it alone. At Kabbage, you will find low ego individuals who work hard to communicate effectively and work collaboratively.


Kabbage is an equal opportunity employer. At Kabbage we make all employment decisions, which include hiring, promoting, transferring, demoting, evaluating, compensating and separating, without regard to sex, sexual orientation, gender identity, race, color, religion, age, national origin, pregnancy, citizenship, disability, service in the uniform services, or any other classification protected by federal, state or local law.