Recommendations Research Team Lead

JOB DESCRIPTION

Lightricks is a company driven by its tech, innovation and good people. At Lightricks Research we are building the algorithms fueling the magic in our apps. Part of our efforts are aimed at assisting our customers to discover that magic and to express their creativity through our many apps.

As we are ramping up our initiative to customize the way we expose our customers to new content and to personalize it by incorporating their own content into it, we are looking for an experienced researcher to lead the efforts in content analysis and recommendations. We're looking for researchers with a passion for what they do, chasing the perfect result even through the difficulties of an innovative research project. As a recommendations team lead at Lightricks Research, you will lead a group of excellent researchers engaging in tasks ranging from representation learning to recommendation systems. You will be able to shape the way our engineering teams build the data pipelines for such systems and decide what types of analysis should be performed at each stage. If you’re looking to make a difference and can bring your expertise to the team, this is the job for you.

RESPONSIBILITIES

  • Managing a team of 3-6 researchers, mentoring them in their research projects and being responsible for their growth.
  • Overseeing the algorithmic portion of our recommendation systems for multiple apps with varying use cases.
  • Conducting applied research, keeping in mind the constraints and requirements of real world solutions.
  • Actively participating in tech transfer of new research into products.
  • Working with engineers, designers and product managers to aim your research to the right place.
  • Exposing the team members to new research developments in their field.
  • Maintaining efficient workflows in your and your team’s research process, using best practices and tools.

PREFERRED REQUIREMENTS

  • M.Sc or Ph.D. degree in a technical field from a top tier university or equivalent experience.
  • 3+ years of experience with recommendation systems, including deep recommendation systems.
  • 1+ years experience leading a project or a team of other researchers.
  • Demonstrated ability to generate new ideas and innovate.
  • Research track record including main contributions to projects you can showcase, peer-reviewed research publications, etc.
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