Data Annotation Associate

22 hours ago

Greater Bengaluru Area, India Stealth AI Startup Full time ₹ 2,00,000 - ₹ 6,00,000 per year

About the Role : Data Annotation Associate

Location: Bengaluru ( Onsite )

Experience: 0–2 years

Employment Type: Full-time / Internship

About the Role

We are looking for Data Annotation Associates to help train next-generation Speech and Video AI models.

In this role, you'll be responsible for labeling, categorizing, and validating data that powers machine learning systems — ensuring accuracy, consistency, and quality across multiple datasets.

This is a great opportunity for individuals who are detail-oriented, tech-curious, and interested in the fast-growing field of AI model training and data operations.

Key Responsibilities

  • Accurately annotate and label speech, video, and image datasets for AI model training.
  • Tag, segment, and categorize data according to project-specific guidelines.
  • Conduct quality checks and audits to ensure consistency and precision.
  • Collaborate with AI engineers and data scientists to improve labeling workflows.
  • Maintain documentation of labeling standards, issues, and quality metrics.
  • Identify and report data inconsistencies or ambiguities to the QA or AI team.
  • Support continuous improvement of annotation tools, processes, and labeling quality.

Skills & Qualifications

  • Bachelor's degree in Computer Science, Data Science, Linguistics, or any relevant field (graduates from all backgrounds with strong analytical skills are welcome).
  • Attention to detail and ability to follow structured instructions precisely.
  • Familiarity with AI/ML concepts, data labeling, or speech/video datasets is a plus.
  • Good communication and documentation skills.
  • Basic understanding of data formats (audio, video, text) and annotation tools.
  • Comfortable with repetitive yet critical data operations and meeting quality benchmarks.

Preferred (Good-to-Have)

  • Prior experience working on speech, NLP, or video annotation projects.
  • Exposure to tools like Labelbox, CVAT, Supervisely, Amazon SageMaker Ground Truth, or similar.
  • Basic understanding of AI model pipelines and machine learning workflows.
  • Knowledge of regional Indian languages (for speech/language datasets) is a plus.

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