Senior Data Labeling Jobs in San Diego

Senior data labeling jobs in San Diego at Rex.zone focus on improving training data quality for AI/ML systems through data labeling, RLHF evaluation, QA review, and prompt evaluation. You will help power LLM training pipelines and computer vision annotation workflows by applying annotation guidelines compliance, resolving edge cases, and driving model performance improvement with high-signal labeled datasets. This role supports AI labs, tech startups, and annotation vendors building NLP, content safety, and multimodal models—fully remote, full-time, and designed for experienced annotators who can lead quality, consistency, and throughput.

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Senior Data Labeling Jobs in San Diego

Title: Senior Data Labeling Specialist (San Diego) 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, LLM training pipelines Salary Currency: USD Salary Min: 63360 Salary Max: 126720 Pay Period: YEAR

About the Role

You will deliver high-precision data labeling and evaluation for AI/ML training workflows. Day-to-day work includes labeling text, image, and multimodal data; performing RLHF preference ranking; conducting QA evaluation for guideline compliance; and supporting prompt evaluation for large language model evaluation. You will document edge cases, propose taxonomy improvements, and partner with operations and engineering stakeholders to improve training data quality, reduce ambiguity, and strengthen model behavior.

What You Will Do

["Execute senior-level data labeling for NLP, computer vision, and content safety datasets","Perform RLHF ranking and large language model evaluation to improve helpfulness, harmlessness, and instruction-following","Run QA evaluation audits for annotation guidelines compliance and consistency across annotators","Handle complex edge cases: ambiguity, multi-intent prompts, policy-sensitive content, and long-context labeling","Create clear written rationales for labels to support error analysis and model performance improvement","Calibrate with teammates using gold sets, adjudication, and disagreement analysis","Identify annotation tooling friction and suggest workflow improvements that increase accuracy and throughput","Maintain strong privacy, security, and content-handling practices while working remotely"]

Required Qualifications

["Mid-Senior experience in data labeling, data annotation, or ML data operations","Proven ability to follow and refine annotation guidelines with high precision","Experience with QA evaluation, audit sampling, and quality scoring methodologies","Familiarity with RLHF, preference ranking, or prompt evaluation for LLM training pipelines","Comfort working with NLP tasks such as named entity recognition, classification, and summarization evaluation","Strong written reasoning skills for label justifications and adjudication notes","Ability to work independently in a remote, full-time environment with reliable availability"]

Preferred Qualifications

["Hands-on experience with computer vision annotation (bounding boxes, polygons, segmentation, keypoints)","Background in content safety labeling (hate, harassment, self-harm, sexual content, regulated goods)","Experience with multilingual labeling or dialect-aware evaluation","Exposure to model evaluation metrics, error taxonomy building, or red teaming workflows","Experience collaborating with AI labs, tech startups, BPOs, or annotation vendors"]

Work Model and Location

["Remote role: Yes (Remote Type: Remote)","Target market/keyword coverage: San Diego, US","Employment type: FULL_TIME","Common modifiers supported: remote, full-time, contract, freelance, entry-level, senior (role is Mid-Senior)"]

Compensation

["Salary Currency: USD","Pay Period: YEAR","Salary Range: 63360 to 126720","Compensation varies by skills alignment, evaluation complexity, and quality performance"]

How to Apply

["Apply through Rex.zone to be matched with senior data labeling projects aligned to your skills","Complete a skills screening focused on training data quality, QA evaluation, and RLHF-style judgments","Start on calibrated tasks with clear annotation guidelines and ongoing feedback loops"]

Frequently Asked Questions

  • Q: Are these senior data labeling jobs in San Diego remote?

    Yes. Remote Type is Remote and the role is designed to be performed fully remotely while targeting candidates searching for senior data labeling jobs in San Diego.

  • Q: What kind of tasks will I work on?

    Typical tasks include data labeling for NLP and computer vision annotation, content safety labeling, named entity recognition, RLHF preference ranking, prompt evaluation, and QA evaluation to improve training data quality in LLM training pipelines.

  • Q: Is this role full-time or contract?

    This posting is FULL_TIME. Rex.zone may also list contract and freelance roles, but this job is explicitly full-time and remote.

  • Q: What does 'Mid-Senior' mean for experience level here?

    Mid-Senior indicates you can handle complex edge cases, apply annotation guidelines compliance consistently, and contribute to quality systems such as audits, adjudication, and model performance improvement workflows.

  • Q: Which domains are most relevant?

    You may work across NLP, computer vision, content safety, and large language model evaluation, depending on project needs from AI labs, tech startups, and annotation vendors.

  • Q: What skills should match the job title and keyword intent?

    Key skills include data labeling, RLHF, QA evaluation, prompt evaluation, named entity recognition, computer vision annotation, content safety labeling, and LLM training pipelines.

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