Senior Data Annotation Jobs in Miami

Senior data annotation jobs in Miami focus on building and evaluating high-quality training datasets for modern AI/ML systems. On Rex.zone, you will support LLM training pipelines through data labeling, RLHF, prompt evaluation, and QA evaluation to improve model performance and reduce risk. This role connects annotation guidelines compliance with real-world workflows like named entity recognition, computer vision annotation, and content safety labeling, ensuring training data quality across multilingual and multi-domain tasks. If you are looking for full-time remote work with Miami-based talent pools and global AI teams, explore this Rex.zone posting and apply to help ship reliable large language model evaluation at scale.

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Job Heading: Senior Data Annotation Jobs in Miami

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

About the Role

You will lead and execute data annotation and evaluation work that directly impacts AI/ML model behavior. This includes writing and enforcing annotation guidelines, performing RLHF preference ranking, grading prompt-response quality, and running QA evaluation loops to improve training data quality. You will collaborate with operations, research, and engineering partners to resolve ambiguity, calibrate labeler agreement, and deliver datasets optimized for model performance improvement across LLM training pipelines.

Key Responsibilities

["Own annotation guidelines compliance and continuously refine rubrics for high-agreement labeling","Perform RLHF tasks including preference ranking, justification writing, and edge-case adjudication","Execute prompt evaluation and response grading across safety, factuality, instruction-following, and style dimensions","Run QA evaluation workflows: sampling plans, error taxonomies, inter-annotator agreement checks, and corrective actions","Support named entity recognition and information extraction labeling for NLP datasets","Deliver computer vision annotation where needed (bounding boxes, polygons, keypoints, segmentation masks) with consistent ontology usage","Perform content safety labeling for policy-aligned datasets (toxicity, harassment, self-harm, sexual content, violence)","Partner with engineering to improve tooling, audits, and data pipelines for scalable labeling operations","Document decisions and escalate ambiguous cases to maintain consistency across annotators and projects"]

Required Qualifications

["Mid-Senior experience in data annotation, data labeling, or AI/ML evaluation programs","Strong understanding of training data quality concepts and how labels affect model behavior","Demonstrated experience with QA evaluation methods (sampling, calibration, agreement measurement, error analysis)","Experience with at least one domain: NLP (NER, classification), LLM evaluation (prompt evaluation, RLHF), computer vision annotation, or content safety labeling","Ability to follow and improve annotation guidelines compliance with clear written communication","Comfort working in remote, metrics-driven production environments with tight iteration cycles"]

Preferred Qualifications

["Hands-on experience with RLHF pipelines and preference data collection for large language models","Background in trust & safety, policy labeling, or content moderation operations","Familiarity with dataset versioning, auditing, and evaluation set construction","Experience mentoring annotators or serving as a lead reviewer in QA workflows","Exposure to multilingual annotation or Miami-area bilingual datasets (English/Spanish) for NLP tasks"]

Work Model and Location

["Remote Type: Remote (must remain Remote)","Location target: Miami, Florida talent market; collaboration is remote-first","Schedule: Full-time availability with overlap for reviews and calibration sessions"]

How You Will Be Evaluated

["Annotation accuracy and consistency against guidelines","Quality of RLHF and prompt evaluation reasoning","QA evaluation rigor: audit quality, error categorization, and measurable process improvements","Throughput balanced with training data quality","Ability to resolve ambiguity and improve documentation for future labelers"]

Why Rex.zone

["Rex.zone connects experienced annotators with AI labs, tech startups, and annotation vendors","Work on real LLM training pipelines, evaluation datasets, and content safety labeling programs","Clear expectations around quality, audits, and annotation guidelines compliance","Opportunity to contribute to model performance improvement through high-impact data work"]

Apply

["Search and apply on Rex.zone using the keyword: Senior Data Annotation Jobs in Miami","Prepare examples of QA evaluation work, guideline writing, or adjudication decisions","Highlight experience across RLHF, prompt evaluation, NER, computer vision annotation, or content safety labeling"]

Frequently Asked Questions

  • Q: Are these senior data annotation jobs in Miami remote?

    Yes. The Remote Type is Remote, and the role is designed for remote-first workflows while targeting the Miami, Florida talent market.

  • Q: What kind of annotation work is included?

    Typical work includes data labeling, RLHF preference ranking, prompt evaluation, QA evaluation, named entity recognition, computer vision annotation, and content safety labeling depending on project needs.

  • Q: What does QA evaluation mean in data annotation?

    QA evaluation includes audits, calibration, inter-annotator agreement checks, error taxonomy tracking, and corrective actions to ensure training data quality and annotation guidelines compliance.

  • Q: Is this role full-time and senior-level?

    Yes. Employment Type is FULL_TIME and Experience Level is Mid-Senior, aligned to senior data annotation job intent.

  • Q: What industries hire for this role through Rex.zone?

    Common employer types include AI labs, tech startups, BPOs, and annotation vendors building LLM training pipelines, NLP systems, computer vision models, and content safety tooling.

  • Q: Do you accept contract or freelance applicants?

    This posting is configured as FULL_TIME. Rex.zone may also list contract or freelance roles separately, but this role’s employment type should be treated as full-time.

  • Q: What skills should I highlight to rank well for this job?

    Highlight data annotation, data labeling, RLHF, prompt evaluation, QA evaluation, LLM evaluation, named entity recognition, computer vision annotation, content safety labeling, annotation guidelines compliance, training data quality, and model performance improvement.

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