Modern Intelligence is hiring a

Data Labeler

Austin, United States
Full-Time
Modern Intelligence is a leading AI company dedicated to harnessing the power of data to drive innovation and make a positive impact on the world. We are seeking two Data Labeling Interns to join our team and contribute to our exciting projects that involve machine learning and artificial intelligence.

Job Description

  • As a Data Labeling Intern at Modern Intelligence, you will play a critical role in helping to curate and annotate datasets that are essential for training machine learning models. In addition to data labeling, you will have the opportunity to support machine learning and software engineering projects during inactive periods of data labeling. 

Key Responsibilities

  • Annotate and label data according to specified guidelines and criteria
  • Ensure the accuracy and consistency of labeled data
  • Perform QA/QC functions to improve data quality
  • Oversee the implementation, maintenance, and optimization of the data labelling SDK
  • Collaborate with cross-functional teams to understand project requirements.
  • Report any issues or inconsistencies encountered during the labeling process
  • Work with data labeling tools and platforms to efficiently label data
  • Support machine learning and software engineering projects during periods of low data labeling activity

Requirements

  • Currently pursuing a B.S./B.A./M.A. degree, or a recent graduate, in Computer Science, Geospatial Science, Geography, or a related field.
  • Strong attention to detail and the ability to maintain high levels of accuracy.
  • Basic understanding of data labeling concepts and techniques.
  • Excellent communication and collaboration skills.
  • Python programming experience

Nice to Have:

  • Familiarity with machine learning concepts (e.g., object detection, segmentation, classification).
  • Geospatial and remote sensing experience (e.g., satellite, aerial, drone).

Modern Intelligence is an equal opportunity employer. We welcome applications from candidates of all backgrounds and experiences
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