Machine Learning Engineer
Palo Alto, CA
Engineering & IT – R&D
Bill.com is a leader in financial process automation for small businesses and mid-size companies. Making it simple to connect and do business, the Bill.com Back Office Cloud digitizes, automates and simplifies legacy payment and financial processes. With an integrated, end-to-end platform, Bill.com leverages artificial intelligence to reduce manual work, and provides a cloud workspace to help run your business anytime, anywhere. The company partners with many of the largest U.S. financial institutions, more than 70% of the top 100 U.S. accounting firms, and major accounting software providers. Bill.com manages more than $70B in annual payment volume across ACH, virtual cards, checks, and international payments. The company has offices in Palo Alto, California and Houston, Texas. For more information, visitwww.bill.com or follow @billcom.
Mission: Bill.com 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 Bill.com.
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 Bill.com (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
● 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