Senior Data Labeling Jobs in Hamburg

Senior data labeling roles at Rex.zone focused on building high-quality training datasets for AI/ML systems. You will support LLM training pipelines through data labeling, RLHF (Reinforcement Learning from Human Feedback), prompt evaluation, and QA evaluation to improve model performance. This remote, full-time job is designed for Mid-Senior professionals who can apply annotation guidelines compliance, resolve edge cases, and run training data quality reviews across NLP, computer vision annotation, and content safety labeling workflows. Explore and apply via Rex.zone to help AI labs, tech startups, and annotation vendors ship safer, more accurate models.

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Senior Data Labeling Jobs in Hamburg

Title: Senior Data Labeling Specialist 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 Labeling, RLHF, QA Evaluation, Prompt Evaluation, Named Entity Recognition, Computer Vision Annotation, Content Safety Labeling, Annotation Guidelines Compliance Salary Currency: USD Salary Min: 63360 Salary Max: 126720 Pay Period: YEAR

About the Role

As a Senior Data Labeling Specialist, you will lead complex annotation and evaluation work that directly impacts training data quality and large language model evaluation outcomes. You will label and review text, image, and multimodal datasets; perform RLHF preference ranking and prompt evaluation; and partner with QA to ensure annotation guidelines compliance. Your work will support model performance improvement across NLP tasks (e.g., named entity recognition), computer vision annotation (e.g., bounding boxes, polygons), and content safety labeling (e.g., policy-aligned categorization). This is a remote, full-time role listed on Rex.zone for candidates searching for senior data labeling jobs in Hamburg.

What You Will Do

You will execute and review data labeling across NLP, computer vision, and content safety domains; run QA evaluation and adjudicate disagreements to improve inter-annotator agreement; perform RLHF preference labeling and write rationale aligned to rubric requirements; complete prompt evaluation tasks to assess helpfulness, harmlessness, and instruction-following; validate training data quality using sampling plans, error taxonomies, and root-cause analysis; maintain annotation guidelines compliance and propose guideline updates for edge cases; collaborate with engineering and data ops to improve tooling, throughput, and auditability; document decisions to support reproducible LLM training pipelines.

Required Qualifications

Mid-Senior experience in data labeling, data annotation, or AI/ML evaluation; strong understanding of annotation guidelines compliance, QA evaluation, and training data quality practices; hands-on exposure to RLHF workflows such as preference ranking and rubric-based scoring; familiarity with NLP concepts including named entity recognition and taxonomy design; familiarity with computer vision annotation formats and quality checks; experience with content safety labeling, policy interpretation, and escalation workflows; ability to communicate edge cases clearly and write consistent rationales; comfort working in remote, cross-functional teams and meeting full-time production targets.

Nice to Have

Experience supporting AI labs, tech startups, BPOs, or annotation vendors; exposure to multilingual labeling or locale-specific evaluation; experience designing QA programs (gold sets, audits, calibration sessions); familiarity with prompt libraries and evaluation harnesses for large language model evaluation; experience improving model performance improvement metrics by targeting recurring annotation errors; comfort reading basic analytics (agreement scores, defect rates, queue health).

Why This Role at Rex.zone

Rex.zone is a platform where professionals find remote, full-time and contract data labeling work across NLP, computer vision, and content safety. In this senior data labeling job track, you will work on real-world LLM training pipelines, focusing on training data quality and QA evaluation to drive measurable model performance improvement. You will be part of a remote team that values consistent annotation guidelines compliance, clear documentation, and scalable workflows.

How to Apply

Apply through Rex.zone with a resume that highlights data labeling, RLHF, QA evaluation, and prompt evaluation experience. Include examples of annotation guidelines compliance work, training data quality audits, named entity recognition projects, computer vision annotation tasks, or content safety labeling decisions. If you have supported full-time, contract, or freelance annotation programs, describe your throughput, accuracy, and calibration practices.

Frequently Asked Questions

  • Q: Is this role remote or on-site in Hamburg?

    The role is explicitly Remote. The page targets senior data labeling jobs in Hamburg for SEO and candidate intent, but the work arrangement remains Remote.

  • Q: What type of data labeling work will I do?

    You may work across NLP labeling (including named entity recognition), RLHF preference ranking, prompt evaluation, QA evaluation, computer vision annotation, and content safety labeling, depending on project needs.

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

    This posting is FULL_TIME. Rex.zone may also host contract and freelance roles, but this job is full-time as specified.

  • Q: What does Mid-Senior mean for this senior data labeling job?

    Mid-Senior indicates you can independently execute complex labeling and evaluation tasks, interpret guidelines, resolve edge cases, and contribute to training data quality and annotation guidelines compliance improvements.

  • Q: How does this job connect to LLM training pipelines?

    Your annotations, RLHF rankings, and QA evaluation outputs become supervised signals and evaluation datasets that influence large language model evaluation outcomes and model performance improvement.

  • Q: What skills should I highlight on my application?

    Highlight Data Labeling, RLHF, QA Evaluation, Prompt Evaluation, Named Entity Recognition, Computer Vision Annotation, Content Safety Labeling, and Annotation Guidelines Compliance, aligned with your real project experience.

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50+Countries Represented

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