Work With Us

< Back to all jobs

NLP Algorithms Engineer

Recommendations

Positions
1
Close Date
5/1/2017
Location
Netanya

Since 2006 Outbrain has been developing a content discovery platform guided by a single mission: to help people discover content that they can trust to be interesting, relevant, and timely. Today our recommendations reach hundreds of millions of users across a global list of premium media properties.

Outbrain is looking for an experienced engineer/researcher to assist in the development of natural language algorithms and software to support its recommendations infrastructure.

Candidates must be fluent with modern statistical NLP techniques for processing textual content, including named entity recognition, clustering, classification, and topic modeling.

We are looking for a candidate who can develop solutions from ideation to full production code, building software that implements sound algorithms while being robust, scalable and high-performance.  

Work in an agile environment – fast development and deployment cycles enabling immediate feedback 

 

Requirements:

  • B.Sc. or higher in Computer Science / Statistics / Mathematics
  • Knowledge of statistical NLP / Machine learning techniques
  • Experience in development of statistical NLP solutions in the industry 
  • Experience in software development in the industry
  • Strong Java Development skills

 


Drive More Traffic

Get links to your content recommended across more than 100,000 publisher sites. It's easy to get started with low daily budgets and flexible CPCs.

Get Started

Game For More Traffic?

The Outbrain Challenge.

Steve Strauss, The SelfEmployed.com & Senior Small Biz columnist, USA TODAY, took the Great Outbrain Challenge.

Read On

400+ Employees & Growing

We're Hiring

We're looking for more great folks to join our team worldwide and if you're "Outbrainy," we want you.

Apply now

What's New at Outbrain

Outbrain + Visual Revenue, Inc.

Outbrain is happy to announce the acquisition of Visual Revenue, a union of content discovery and editorial decision support.

Learn more