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# Software Engineer

- **Company:** Datavisor, Inc.
- **Location:** United States
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Bash Shell, Big Data, Nvidia CUDA, Databases, Relational Databases, Fraud Prevention and Detection, Apache Hadoop, Apache HBase, Hibernate (Java), Intrusion Detection and Prevention, Spring Framework, Python (Programming Language), Machine Learning, Object-Relational Mapping, Software Engineering, SQL Databases, Data Streaming, UML, Data Processing, Multithreading, Real Time Systems, Test-Driven Development (TDD), Apache Spark, Deep Learning, Build Management, Apache Flink, Cassandra, Apache Kafka, Machine Learning Operations
- **Published:** July 17, 2026
- **Apply:** https://www.dice.com/job-detail/e8768952-9388-44b4-90f1-88d76c4b76b8

## About the Role

* 1-5 years software development experience
 * 1-5 years experience in Java, Shell, Python development
 * Excellent knowledge of Relational Databases, SQL and ORM technologies (JPA2, Hibernate) is a plus
 * Experience in Cassandra, HBase, Flink, Spark or Kafka is a plus.
 * Experience in the Spring Framework is a plus
 * Experience with test-driven development is a plus

Preferred Qualifications

 * Worked on multithreaded applications i
 * Experience in Shell and Python
 * Experience in Kubernates
 * Experience in CUDA development is a plus

## Description

As platform engineers, we are building 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 engineers to help us expand our novel streaming and database systems, which enable our detection capabilities.

We continue to push the boundary of what's possible in fraud detection and data processing at scale. Join us to help usher in more innovative solutions to the fraud detection space.

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 real-time streaming technologies (e.g. Kafka, Flink)


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