Software Engineer Internship

4 Months ago • All levels

Software Development & Engineering

Job Description

As a platform engineer intern, you will learn how to build a next-generation machine learning platform. This platform incorporates unsupervised machine learning (UML) and supervised machine learning (SML) algorithms. The team works to improve core detection algorithms and automate the training process. The platform team develops the architecture that makes real-time UML possible. The role involves designing and building machine learning systems to process data sets, utilizing unsupervised, supervised, and deep learning to detect fraudulent behavior. Responsibilities include building and optimizing systems, tools, and validation strategies, helping design and build distributed real-time systems, and using big data technologies to build large-scale machine learning pipelines. The internship is ideal for those majoring in Computer Science or Computer Engineering.

Must Have:

Design and build machine learning systems.
Use machine learning to detect fraudulent behavior.
Build and optimize systems, tools, and strategies.

Add these skills to join the top 1% applicants for this job

data-analytics

hbase

hadoop

spark

deep-learning

cassandra

algorithms

machine-learning

DataVisor is a next generation security company that utilizes industry leading unsupervised machine learning to detect fraudulent activity for financial transactions, mobile user acquisition, social networks, commerce and money laundering. Our solution is used by some of the largest internet properties in the world, including Pinterest, FedEx, AirAsia, Synchrony Financial, Zomato and Ping An, to protect them from the ever-increasing risk of fraud. Our award-winning software is powered by a team of world-class experts in big data, security, and scalable infrastructure. Our culture is open, positive, collaborative, and results driven. Come join us!

Summary

As a platform engineer intern, you will learn how to build a next-generation machine learning platform, which incorporates our secret sauce, UML (unsupervised machine learning) with other SML (supervised machine learning) algorithms. Our team works to improve our core detection algorithms and automate the full training process. As complex fraud attacks become more prevalent, it is more important than ever to detect fraudsters in real-time. The platform team is responsible for developing the architecture that makes real-time UML possible. We are looking for creative and eager-to-learn engineers to help us expand our novel streaming and database systems, which enable our detection capabilities.

This position is ideal for those who are majoring in Computer Science or Computer engineering who would like to gain some hands-on experience in fraud detection and machine learning before graduation. This 3 to 6 months internship could lead to a full-time position after graduation.

What you'll do:

Design and build machine learning systems that process data sets from the world’s largest consumer services
Use unsupervised machine learning, supervised machine learning, and deep learning to detect fraudulent behavior and catch fraudsters
Build and optimize systems, tools, and validation strategies to support new features
Help design/build distributed real-time systems and features
Use big data technologies (e.g. Spark, Hadoop, HBase, Cassandra) to build large scale machine learning pipelines
Develop new systems on top of realtime streaming technologies (e.g. Kafka, Flink)