AI Data Labeling Jobs in India
AI Data Labeling Jobs in India (Remote, Full-Time)
Support real-world AI/ML training workflows by producing high-quality labeled datasets for large language models and computer vision systems. You will follow annotation guidelines, perform QA evaluation, and contribute to RLHF and prompt evaluation tasks that improve model performance, safety, and reliability.
Key Responsibilities
ā¢ Create high-quality labels for NLP tasks (text classification, named entity recognition, prompt evaluation, summarization evaluation)
ā¢ Perform RLHF-style ranking and preference labeling to support model alignment and instruction following
ā¢ Execute QA evaluation workflows (gold set checks, inter-annotator agreement, consistency checks, error analysis)
ā¢ Apply annotation guidelines, resolve edge cases, and document decisions with clear rationale
ā¢ Support content safety labeling (toxicity, self-harm, harassment, policy categories)
ā¢ Contribute to computer vision annotation (image classification, bounding boxes, polygons, segmentation) as needed
ā¢ Track productivity and quality metrics and collaborate with reviewers to improve outcomes
What We Look For
ā¢ Experience in data labeling, data annotation, or AI/LLM evaluation
ā¢ Strong attention to detail and ability to apply complex guidelines consistently
ā¢ Comfort with QA evaluation, calibration sessions, and feedback-based improvement
ā¢ Familiarity with NLP and/or computer vision annotation; content safety experience is a plus
Work Model
Remote, full-time role with structured QA and reviewer feedback loops.
Projects may include task-queue workflows, but employment type remains FULL_TIME.
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Apply To this Job
Support real-world AI/ML training workflows by producing high-quality labeled datasets for large language models and computer vision systems. You will follow annotation guidelines, perform QA evaluation, and contribute to RLHF and prompt evaluation tasks that improve model performance, safety, and reliability.
Key Responsibilities
ā¢ Create high-quality labels for NLP tasks (text classification, named entity recognition, prompt evaluation, summarization evaluation)
ā¢ Perform RLHF-style ranking and preference labeling to support model alignment and instruction following
ā¢ Execute QA evaluation workflows (gold set checks, inter-annotator agreement, consistency checks, error analysis)
ā¢ Apply annotation guidelines, resolve edge cases, and document decisions with clear rationale
ā¢ Support content safety labeling (toxicity, self-harm, harassment, policy categories)
ā¢ Contribute to computer vision annotation (image classification, bounding boxes, polygons, segmentation) as needed
ā¢ Track productivity and quality metrics and collaborate with reviewers to improve outcomes
What We Look For
ā¢ Experience in data labeling, data annotation, or AI/LLM evaluation
ā¢ Strong attention to detail and ability to apply complex guidelines consistently
ā¢ Comfort with QA evaluation, calibration sessions, and feedback-based improvement
ā¢ Familiarity with NLP and/or computer vision annotation; content safety experience is a plus
Work Model
Remote, full-time role with structured QA and reviewer feedback loops.
Projects may include task-queue workflows, but employment type remains FULL_TIME.
Apply tot his job
Apply To this Job