AI Data Labeling Jobs India

AI Data Labeling Jobs India at Rex.zone focus on training-data production for modern AI/ML systems, including data labeling, RLHF scoring, prompt evaluation, and QA evaluation for large language model training pipelines. You will apply annotation guidelines compliance to improve training data quality, reduce model errors, and support model performance improvement across NLP, computer vision annotation, named entity recognition, and content safety labeling workflows. This remote, full-time role supports distributed annotation teams and delivers measurable quality metrics for LLM evaluation, dataset curation, and safety policy enforcement on Rex.zone.

AI Data Labeling Jobs India — Job Overview

About the Role

You will produce and evaluate high-quality labeled datasets used in AI training pipelines. Work includes text and multimodal data labeling, RLHF preference ranking, prompt-response evaluation, and content safety labeling. You will collaborate with reviewers and tooling teams to ensure consistent annotation guidelines compliance, strong inter-annotator agreement, and traceable QA evaluation outcomes.

What You Will Do

Core responsibilities include: creating labels for NLP tasks (classification, NER, summarization, intent), performing RLHF ranking and rubric-based scoring, running QA evaluation checks and adjudication, documenting edge cases and updating annotation guidelines, validating training data quality using sampling and error analysis, supporting model performance improvement by flagging systematic model failures, and contributing to dataset curation for computer vision annotation and multimodal tasks when required.

Workstreams You May Support

Depending on project assignment, you may support: LLM training pipelines (instruction tuning, preference data, safety data), named entity recognition datasets (people, orgs, locations, medical or finance entities), computer vision annotation (bounding boxes, polygons, keypoints, segmentation masks), prompt evaluation (helpfulness, harmlessness, truthfulness, style), content safety labeling (policy classification, sensitive content detection), and QA evaluation (gold set checks, audit trails, reviewer calibration).

Requirements

Required qualifications: experience with data labeling or annotation operations, strong written English with rubric-based judgment, ability to follow detailed annotation guidelines compliance, familiarity with NLP concepts and LLM evaluation, comfort with repetitive QA evaluation workflows, and proficiency with web-based annotation tools and spreadsheets. Mid-Senior expectations include mentoring annotators, participating in calibration sessions, and proposing guideline clarifications to improve training data quality.

Preferred Qualifications

Preferred: hands-on experience with RLHF workflows, prompt-response evaluation, content safety labeling, NER tagging schemes (BIO/BILOU), computer vision annotation types, quality measurement (precision/recall concepts, agreement metrics), and experience working with global remote annotation teams or annotation vendors/BPOs.

Quality and Metrics

You will be measured on training data quality, annotation guidelines compliance, throughput with sustained accuracy, error rate reduction, audit readiness, reviewer feedback incorporation, and contributions to model performance improvement through clear issue reports and consistent rubric application.

Remote Work and Collaboration

This is a Remote, FULL_TIME role. Collaboration includes async reviews, calibration meetings, QA evaluation audits, and structured feedback loops. You will coordinate with project leads, quality reviewers, and tooling engineers to keep datasets consistent and scalable.

How to Apply on Rex.zone

Explore AI data labeling jobs India on Rex.zone, review project requirements, and submit your application with relevant annotation experience. If selected, you will complete a qualification task aligned with RLHF, data labeling, and QA evaluation standards.

Related Job Modifiers and Opportunities

Rex.zone also supports remote, contract, freelance, full-time, entry-level, and senior opportunities depending on project demand. Domains may include NLP, computer vision annotation, content safety labeling, LLM training pipelines, and QA evaluation across AI labs, tech startups, and annotation vendors.

Frequently Asked Questions

Q: What are AI data labeling jobs in India?
AI data labeling jobs in India involve creating and validating labeled datasets (text, images, audio, multimodal) used to train and evaluate AI/ML models. Typical work includes data annotation, named entity recognition, computer vision annotation, prompt evaluation, RLHF preference ranking, and QA evaluation to improve training data quality.
Q: Is this role remote and full-time?
Yes. The role is explicitly Remote and FULL_TIME, with delivery tracked through quality metrics, audit checks, and project milestones.
Q: What is RLHF and how does it relate to data labeling?
RLHF (Reinforcement Learning from Human Feedback) uses human judgments—like preference ranking and rubric-based scoring—to train models to produce better responses. In practice, it is a specialized form of labeling focused on evaluating model outputs for helpfulness, safety, and correctness.
Q: What skills are most important for AI data labeling jobs India?
Key skills include AI data labeling, data annotation, annotation guidelines compliance, training data quality judgment, QA evaluation, prompt evaluation, and familiarity with NLP/LLM evaluation. For some projects, named entity recognition and computer vision annotation are important.
Q: What tools will I use for annotation work?
You will typically use web-based annotation tools, quality review dashboards, and spreadsheet-style reporting to track labeling decisions, QA evaluation outcomes, and guideline updates.
Q: Do you hire entry-level candidates for data labeling?
Project demand varies. Rex.zone may list entry-level, mid-level, or senior roles. This posting is Mid-Senior; however, related remote, contract, freelance, and entry-level opportunities may be available depending on current programs.
Q: What kinds of datasets will I work on?
Datasets may include NLP classification, named entity recognition, instruction-following prompts, content safety labeling sets, and computer vision annotation tasks, all designed to support LLM training pipelines and model performance improvement.
Q: How is quality evaluated in data labeling projects?
Quality is evaluated through QA evaluation processes such as gold set accuracy, calibration rounds, audit sampling, reviewer adjudication, and consistency checks to ensure annotation guidelines compliance and high training data quality.
Q: Where do I apply for AI data labeling jobs India?
Apply via Rex.zone by selecting the relevant AI data labeling jobs India listing, completing required screening questions, and submitting any requested work samples or qualification tasks.

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