Senior Machine Learning Engineer- Machine Learning Platform - job 10 of 12
Visa is a world leader in digital payments, facilitating more than 215 billion payments transactions between consumers, merchants, financial institutions, and government entities across more than 200 countries and territories each year. Our mission is to connect the world through the most innovative, convenient, reliable, and secure payments network, enabling individuals, businesses, and economies to thrive.
When you join Visa, you join a culture of purpose and belonging – where your growth is priority, your identity is embraced, and the work you do matters. We believe that economies that include everyone everywhere, uplift everyone everywhere. Your work will have a direct impact on billions of people around the world – helping unlock financial access to enable the future of money movement.
This opportunity is in Visa's Machine Learning Platform. The Machine Learning Platform provides soft infrastructure support to Visa's data scientists and researchers. We enable the training of statistical and machine learning models via development and maintenance of a distributed computing stack. Frameworks used in the stack are: Kubernetes, Ray, Torch, Tensorflow, XGBoost, and Spark. Development is primarily in Python and Go.
We are a cross-functional team that interfaces both with internal data science and research clients as well as other hard and soft infrastructure teams.
Responsibilities include:
--Monitoring of infrastructure health and problem solving to address persistent or urgent issues
--Platform stabilization, including unit and integration testing
--Interfacing with Kubernetes and data platform teams
--Implementation of new infrastructure features
This is a hybrid position. Expectation of days in office will be confirmed by your hiring manager.
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Visa Inc. operates as a payments technology company worldwide. The company facilitates commerce through the transfer of value and information among consumers, merchants, financial institutions, businesses, strategic partners, and government entiti...
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