On-site
Part Time
Overview:
The Data Annotator plays a crucial role in ensuring the accuracy and quality of data used for training machine learning models. This position focuses on labeling and annotating diverse datasets to facilitate advanced data processing and analysis, ultimately contributing to the improvement of AI-driven solutions. Candidates will collaborate with data scientists and machine learning engineers to create high-quality training datasets that enhance model performance.
Key Responsibilities:
Review, annotate, and label datasets according to provided guidelines and specifications.
Ensure consistency and accuracy in data annotation to maintain high-quality standards.
Collaborate closely with team members to understand project requirements and tackle specific data challenges.
Identify and report anomalies or inconsistencies in data that may impact analysis.
Participate in regular training and feedback sessions to enhance annotation skills and techniques.
Utilize annotation tools and software effectively to streamline the workflow.
Technical Skills:
Proficiency in data annotation tools and platforms (e.g., Labelbox, Amazon Sagemaker, VGG Image Annotator).
Familiarity with basic programming concepts and scripting languages (e.g., Python) is a plus.
Understanding of data management and database systems.
Capability to handle large datasets and perform data validation.
Required Qualifications:
A high school diploma or equivalent; a bachelor’s degree in a relevant field is preferred.
Previous experience in data annotation or a related role is advantageous but not mandatory.
Strong attention to detail and a methodical approach to work.
Skills & Experience:
Demonstrated experience in data annotation across various types of media (text, images, audio, etc.).
Excellent organizational and time-management skills.
Strong communication skills to collaborate effectively with team members.
Problem-solving abilities to address challenges that arise during the annotation process.
This position is ideal for individuals who are detail-oriented and passionate about contributing to the advancement of machine learning technologies.
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