AI Jobs in India

AI Jobs in India at Rex.zone focus on search-recognizable roles across LLM training pipelines, RLHF, data labeling, and model evaluation workflows. These remote full-time opportunities support large language model evaluation, prompt evaluation, training data quality, and annotation guidelines compliance for AI labs, tech startups, and annotation vendors. You will contribute to model performance improvement by running QA evaluation, content safety labeling, and structured NLP and computer vision annotation tasks with measurable accuracy targets and production-ready tooling.

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AI Jobs in India — Remote AI Data Annotation Specialist

Date: 25-02-2026 | Company: Rexzone | Country: US | Remote Type: Remote | Employment Type: FULL_TIME | Experience Level: Mid-Senior | Industry: Technology | Job Function: Engineering | Skills: AI data annotation, data labeling, RLHF, LLM evaluation, prompt evaluation, QA evaluation, named entity recognition, computer vision annotation, content safety labeling, annotation guidelines, training data quality, model performance improvement | Salary Currency: USD | Salary Min: 63360 | Salary Max: 126720 | Pay Period: YEAR

About the Role

You will label and evaluate multimodal AI training data (text, image, and structured fields) and perform RLHF-style preference judgments to improve large language model behavior. The role includes prompt evaluation, rubric-based scoring, and QA evaluation to ensure training data quality and annotation guidelines compliance. You will collaborate with engineering to refine task specifications, analyze disagreement, and support model performance improvement through high-signal feedback loops used in LLM training pipelines.

What You Will Do

Execute data labeling and data annotation for NLP and computer vision datasets; perform RLHF comparisons and reward-model preference judgments; run prompt evaluation and response grading using detailed rubrics; complete QA evaluation audits, issue triage, and rework for accuracy targets; apply named entity recognition and taxonomy tagging; conduct content safety labeling (policy, harm, hate, self-harm, sexual content) with escalation workflows; document edge cases and update annotation guidelines; report annotation throughput, agreement rates, and error categories to improve production quality.

What We Are Looking For

Mid-Senior experience delivering high-precision labeling and evaluation work; strong written English and ability to follow complex rubrics; familiarity with LLM evaluation, RLHF concepts, and prompt evaluation methodologies; hands-on experience with named entity recognition, text classification, or computer vision annotation; strong QA mindset (sampling, audits, inter-annotator agreement, root-cause analysis); comfort working remotely with asynchronous communication, versioned guidelines, and production tooling.

Preferred Qualifications

Prior work with annotation vendors, BPO operations, AI labs, or tech startups; experience labeling for content safety and policy enforcement; exposure to evaluation metrics, disagreement analysis, and calibration sessions; basic scripting/SQL for analysis of labeling outputs; understanding of dataset curation, data hygiene, and privacy-safe handling.

Tools and Workflow

Annotation platforms and labeling tools; structured QA evaluation checklists; issue trackers and guideline version control; secure data handling practices; remote collaboration across time zones. Work emphasizes training data quality, annotation guidelines compliance, and repeatable evaluation processes aligned with LLM training pipelines.

Compensation

Salary range: 63360–126720 USD per year (FULL_TIME). Final compensation depends on scope, evaluation complexity (NLP, CV, content safety), and demonstrated QA rigor.

How to Apply

Explore and apply to AI Jobs in India on Rex.zone. Prepare examples of evaluation or labeling work (sanitized), describe your QA evaluation approach, and highlight experience with RLHF, prompt evaluation, named entity recognition, computer vision annotation, or content safety labeling.

Frequently Asked Questions

  • Q: Are these AI Jobs in India remote or onsite?

    These roles are explicitly Remote and designed for distributed delivery of data labeling, RLHF evaluation, and QA evaluation work.

  • Q: What kind of AI work is typical for this posting?

    Typical work includes data annotation, prompt evaluation, LLM evaluation, RLHF preference judgments, named entity recognition, computer vision annotation, and content safety labeling focused on training data quality.

  • Q: Is this job contract, freelance, or full-time?

    This posting is for FULL_TIME employment. Rex.zone may also list contract or freelance roles separately, but the metadata here is unchanged and remains FULL_TIME.

  • Q: What experience level is required?

    The role is Mid-Senior, emphasizing independent execution, strong rubric adherence, and QA evaluation capability in production workflows.

  • Q: Which domains are supported: NLP, computer vision, or content safety?

    All three are supported: NLP (classification, NER), computer vision annotation (bounding boxes/segmentation where applicable), and content safety labeling aligned to policy rubrics.

  • Q: How does RLHF relate to this role?

    You will perform RLHF-style preference comparisons and graded judgments that become training signals for reward modeling and supervised fine-tuning in LLM training pipelines.

  • Q: What does QA evaluation mean in day-to-day work?

    QA evaluation includes audit sampling, guideline compliance checks, disagreement analysis, error categorization, and rework cycles to improve training data quality and model performance improvement.

  • Q: Where do I apply?

    Apply through Rex.zone by selecting the AI Jobs in India listing and submitting your profile with relevant labeling, evaluation, and QA experience.

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