Data Labellers for AI training

Overview

We are seeking a meticulous and attentive Data Labeler to join our team. The ideal candidate will be responsible for tagging and labeling various types of data, including text, images, and videos, to improve the accuracy of our machine learning models. This role requires a keen eye for detail, the ability to work with precision under tight deadlines, and a solid understanding of the specific domain or industry we are focusing on.

Responsibilities

• Accurately label and annotate data according to predefined criteria and guidelines.
• Review and verify data for accuracy and consistency.
• Work closely with data scientists and machine learning engineers to understand the requirements and purposes of data labeling tasks.
• Maintain detailed documentation of labeling guidelines and processes.
• Provide feedback to improve data collection and labeling tools and processes.
• Participate in quality assurance checks to ensure the high quality of labeled data.
• Stay updated on industry trends and advancements in data labeling technologies and methodologies.

Qualifications

• Excellent attention to detail and accuracy.
• Strong analytical and critical thinking skills.
• Ability to work independently and as part of a team.
• Good communication skills, with the ability to clearly explain complex concepts.
• Knowledge of machine learning concepts and the specific domain (e.g., healthcare, finance, automotive) is a plus.

We Offer

• Opportunities for professional development and career growth.
• A dynamic and collaborative work environment.
• Access to cutting-edge technology and methodologies in the field of AI and machine learning.
• Flexible hours
• Working from home

If interested, please fill out this Google form: https://forms.gle/Zjgt7EBEiberwk9A9 . Thank you!

Job Types: Full-time, Part-time

Salary: $8.00 - $12.00 per hour

Expected hours: 20 – 40 per week

Benefits:

• Flexible schedule

Compensation package:

• Bonus opportunities
• Performance bonus

Experience level:

• No experience needed

Schedule:

• 4 hour shift
• 8 hour shift

Work Location: In person