Machine Learning engineer

DESCRIPTION

About us

APIs form the foundation of the application innovation needed to drive business success today. Across banks, retail and transportation, IoT, autonomous vehicles, and smart cities, every web and mobile app depends on APIs. Without secure APIs, businesses cannot rapidly innovate. Salt Security has delivered the only patented solution to identify and prevent API attacks, using Big Data and AI to thwart this top threat to businesses today.

Who We are

At Salt, we’re passionate about what we do. We work as a team and embrace new ideas, wherever they come from. We also enjoy all the benefits of a startup environment, including quickly seeing the results of your work, making an outsized impact on our company, and solving a diverse set of engineering challenges. Want to make a big difference? We encourage you to apply!

About the position

Our research team deals with the extremely challenging aspects of Salt’s cutting edge solution. From inventing and validating new algorithms to delivering advanced insights and analytics, we use our data to level up the security we provide to our customers.

Anomaly detection, classification, prioritization and complex graph analysis problems are our bread and butter. Building advanced ML pipelines alongside keeping our models and algorithms at the state of the art is our continuous challenge. Together with our super talented engineering team, we set the industry bar for AI based API security.

As a Machine-Learning engineer at Salt you will create tools for handling high volume data and feature extraction, as well as design and implement scalable data processing pipelines to facilitate rapid research-to-production ML deployments.

REQUIREMENTS

Who are you?

  • BSc in computer science or related field
  • 5+ years of software engineering experience
  • Experience in writing high-scale, production-level code
  • Experience working with public cloud
  • Self-learner, initiator, able to quickly learn new technologies
  • Experience with training, testing, deployment and monitoring machine learning models in production – advantage
  • Experience with data pipelines / big-data analytics – big advantage
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