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Data Labeling (Part-time position)

Nanit

Nanit

Tel Aviv-Yafo, Israel
Posted on Thursday, July 4, 2024

About Nanit:

The team behind Nanit are experts in those first precious moments of your baby’s life. The company provides products and services that help parents stay informed on their baby’s health, safety and well-being through smarter and better use of technology. In 2016, the Nanit baby monitor revolutionized the industry with computer vision and machine learning capabilities that helped parents help their babies sleep better. Now, the company has become the leader in the connected nursery space, with an incredible customer base of highly engaged new parents who look to Nanit as a source of information and expertise on their parenting journey.

About the job:

We are looking for entry-level candidates for the position of AI Data annotator. Your role at Nanit will be to be part of the data team within the AI group, collaborating closely with the algorithm team.

What you will do:

  • Accurate and timely data labeling using a variety of software tools.
  • Analyzing the labeled data to ensure high quality.
  • Taking part in monitoring the AI models in production using different algorithmic and software tools.
  • Close work with the Algo and MLops teams.

Requirements:

  • No previous experience in Data Labeling is required.
  • Technical orientation and ability to learn and work with software tools.
  • Ability to work independently and as part of a team.
  • Can-do/positive approach.
  • Cultivating both detail-oriented thinking and big-picture thinking.
  • Fluent in English. Native - advantage

Why Nanit:

  • We have an awesome product, that makes life a little more manageable for new parents
  • We work hard. We are constantly striving to discover new and innovative ways to improve our product and ourselves
  • We invest in people. We consider each employee a long-term investment and we see value in continuously nurturing and training them

We believe in creating a fun, ego-less, family-friendly, flexible work environment