Data Annotation Associate
8 hours ago
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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