Job Detail

Machine Learning Engineer at
Palo Alto, CA, US

About is the leading business payments network, with 3 million members paying and getting paid over $52 billion per year. saves companies more than 50% of the time typically spent on financial back-office operations and helps businesses get paid 3 - 4 times faster by automating end-to-end payment processes.  The company is the choice of 4 of the top 10 U.S. banks; leading accounting software providers QuickBooks Online and Xero; and over 50 percent of the top 100 U.S. accounting firms.  It is the only business payments solution endorsed by the American Institute of CPAs (AICPA). The recipient of more than 70 awards, proudly received multiple PC Magazine's Editor's Choice Awards and CEO René Lacerte was recently recognized as an E&Y Entrepreneur of the Year.

Mission: is looking for Python Machine Learning Engineers to join our team and solve challenging, data-driven problems. We are developing new ML models that (1) detect fraudulent transactions and bad actors and (2) extract data from unstructured documents so that customers never enter data. We are also expanding an ML-driven approach to other parts of our business.  

As a Python Machine Learning Engineer, you will partner with a diverse set of teams, including engineers who build the core product experience, money movement system and risk operations.  You will build and deploy machine learning models, and identify new approaches and methodologies for improving the performance of our ML applications. You will make an impact and drive the establishment of machine learning as a practice at 
We have multiple positions available at different levels of seniority.


  • Build machine learning models for fraud detection and document data extraction
  • Drive the definition of the machine learning infrastructure and pipeline to build and scale machine learning at (e.g feature storage, predictions and scoring)
  • Define metrics for feature evaluation and model performance
  • Explore and investigate different model types and techniques to improve machine learning performance
  • Participate in feature engineering and defining data requirements for different models
  • Leverage various AWS technologies for building and deploying models

Desired Experience and Skills:

  • 2+ years of relevant industry experience (MS or PhD preferred but not required)
  • Expertise in python
  • Extensive knowledge of machine learning algorithms, techniques, available implementations in python (e.g NumPy, SciPy, Pandas) and frameworks (e.g tensorflow)
  • Strong point of view on how to build highly scalable machine learning infrastructure
  • Excellent engineering and problem solving skills.  Able to write high performing, high quality code in python
  • Experience with AWS, Sagemaker preferable Culture:

  • Humble – No ego
  • Fun –  Celebrate the moments
  • Authentic – We are who we are
  • Passionate – Love what you do   
  • Dedicated – To each other and the customer