Staff Machine Learning Engineer
Modeling, Risk
Posted on 5/4/2023
San Francisco, CA, USA • Remote in USA
Experience Level
Desired Skills
Apache Spark
Data Structures & Algorithms
Google Cloud Platform
Natural Language Processing (NLP)
  • An advanced degree (M.S., PhD.), preferably in Computer Science,Engineering, Statistics, Physics, Mathematics or a related technical field
  • PhD plus 4 years (or Master plus 6 years) industry working experience in applied Machine learning or Deep learning
  • A strong track record of performing machine learning model development using Python (numpy, pandas, tensorflow, pytorch, scikit-learn, etc.) and SQL/NoSQL interaction patterns
  • Expert level knowledge of modern techniques in machine learning and deep learning, e.g., transformer network architectures, tree models with an orientation to maximizing such algorithms in a large scale production setting
  • Familiarity with Linux/OS X command line, version control software (git), and general software development principles with a machine learning software development life-cycle orientation
  • Machine learning strategic sequencing of methodological and software improvements to work back from maximizing core metrics associated with optimizing the business
  • The ability to clearly communicate complex results to technical and non-technical audiences and stakeholders (PMs, Operations, Engineers)
  • As a Machine Learning Modeler within the Risk Machine Learning and Decision Science team, you work on projects that enable a software driven, machine learning centric view on all money movement and every transaction within the rapidly growing Square ecosystem. This touches on actively maximizing the trade off of revenue growth and risk using artificial intelligence. The machine learning driven software that we release interacts with every transaction and money movement within our seller ecosystem - a profound degree of scale and impact. Such machine learning techniques touch on transfer learning, reinforcement learning, decision theory, deep learning sequence modeling, natural language processing, and optimization theory. In addition, we also strive to provide our sellers, through seller facing products, with transparency around why our machine learning made a particular decision. This touches on algorithms in the relatively new space of explainable artificial intelligence
  • We are seeking a highly motivated and experienced Staff Machine Learning Modeler to join the Payment credit risk team. The successful candidate will lead the development and maintenance of predictive models that drive our credit risk strategies, and will work closely with stakeholders to ensure optimal credit risk management. The successful candidate will play a crucial role in developing and executing the team's roadmap and long term strategy for payment credit risk modeling, and will be responsible for hands-on building and maintaining predictive ML models that drive our credit risk strategies. You are not only an executor but also a visionary leader to drive business and team growth
  • You will:
  • Build machine learning/deep learning models for payment credit risk assessment that analyze seller / payment activity in real time / batch across Seller's ecosystem consisting of payments, banking, and debit card products
Desired Qualifications
  • Familiarity with cloud computing platforms (e.g., AWS, GCP) and big data technologies (e.g., Spark) is a plus

1,001-5,000 employees

Digital payment processor
Company Overview
Square's mission is to ensure that all businesses are able to participate and thrive in the economy. The company is building infrastrucutre for online payments.