Softwares | Data Annotation Specialist_Immediate Joiner

2 days ago

Bengaluru, Karnataka, India YsecIT Full time ₹ 2,50,000 - ₹ 7,50,000 per year

Job Title: Data Annotation Specialist

Department: AI/ML Data Operations

Reports To:

Role Overview

The Data Annotation Specialist will be responsible for creating, labeling, and maintaining high-quality datasets used to train and validate machine learning models. This role requires attention to detail, strong communication skills, and a deep understanding of data quality standards to ensure that AI systems are trained on accurate and representative data.

Key Responsibilities

  • Review, categorize, and label large volumes of text, image, audio, and video data using internal tools and guidelines.
  • Ensure accuracy, consistency, and efficiency in annotation work while meeting project deadlines.
  • Collaborate with data scientists, ML engineers, and project managers to refine labeling criteria and annotation processes.
  • Perform quality assurance checks to ensure annotations meet required performance thresholds.
  • Contribute to documentation of labeling standards, best practices, and guidelines.
  • Identify ambiguities or inconsistencies in data and proactively escalate them for clarification.
  • Support development and testing of automated labeling tools by providing human-verified test datasets.
  • Review and improve workflows to enhance annotation speed and precision.

Required Qualifications

  • Bachelors degree in Computer Science, Information Technology, Data Science, Engineering, or a related field.
  • 0–2 years of experience in data annotation, labeling, or data quality assurance.
  • Practical experience working with annotation tools (e.g., Label Studio, Labelbox, Supervisely, CVAT).
  • Familiarity with common data modalities such as text, audio, and image datasets.
  • Strong attention to detail with excellent organizational and concentration skills.
  • Basic understanding of AI and machine learning concepts.
  • Proficiency with productivity and collaboration tools.

Preferred Qualifications

  • Experience in labeling data for computer vision or NLP tasks (e.g., bounding boxes, entity recognition, sentiment tagging).
  • Familiarity with Python-based data review workflows or annotation APIs.
  • Knowledge of quality control processes such as inter-annotator agreement (IAA).
  • Exposure to LLM training pipelines.

Soft Skills

  • Ability to follow detailed instructions with precision and accountability.
  • Clear communication and ability to collaborate across cross-functional teams.
  • Strong problem-solving attitude and curiosity for AI data operations.
  • Adaptability to changing project requirements and data types.

Performance Indicators

  • Annotation accuracy and consistency scores.
  • Throughput and turnaround time per dataset task.
  • Quality assurance and peer review success rate.
  • Contribution to process documentation and continuous improvement initiatives.

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