[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"job-senior-data-annotation-jobs-boston":3},{"Ques":4,"Slug":25,"Header":26,"job_category":54},{"title":5,"content":6},"Frequently Asked Questions",[7,10,13,16,19,22],{"A":8,"Q":9},"Yes. The Remote Type is Remote and the role is designed for distributed work while aligning to Boston market hiring intent.","Is this role remote even though it targets Boston senior data annotation jobs?",{"A":11,"Q":12},"Typical tasks include data labeling, RLHF preference ranking, prompt evaluation, QA evaluation, named entity recognition for NLP, computer vision annotation, and content safety labeling, depending on the project.","What types of annotation tasks are included?",{"A":14,"Q":15},"Senior work emphasizes handling ambiguity, adjudicating disagreements, improving annotation guidelines compliance, creating gold sets, running calibration, and protecting training data quality for LLM training pipelines.","What does senior-level data annotation mean here?",{"A":17,"Q":18},"This posting is FULL_TIME. Rex.zone may also host contract or freelance roles, but this job’s Employment Type remains FULL_TIME.","Is the position full-time or contract\u002Ffreelance?",{"A":20,"Q":21},"Highlight Data Annotation, Data Labeling, RLHF, QA Evaluation, Prompt Evaluation, Named Entity Recognition, Computer Vision Annotation, Content Safety Labeling, Annotation Guidelines Compliance, Training Data Quality, LLM Evaluation, and LLM Training Pipelines.","What skills should I highlight to be competitive?",{"A":23,"Q":24},"The salary range is 63360 to 126720 in USD, with a YEAR pay period.","What is the compensation range and pay period?","senior-data-annotation-jobs-boston",{"desc":27,"title":28,"content":29},"Senior Data Annotation professionals at Rex.zone support AI\u002FML training workflows by producing high-quality labeled data, RLHF judgments, and QA evaluation signals for large language model evaluation and computer vision annotation. In this remote, full-time role aligned to Boston hiring demand, you will apply annotation guidelines compliance, training data quality checks, and model performance improvement feedback loops across NLP, content safety labeling, prompt evaluation, and named entity recognition tasks. You will collaborate with cross-functional engineering teams, follow gold-standard labeling protocols, and help scale LLM training pipelines through consistent, auditable data labeling operations. Explore and apply via Rex.zone to join teams building reliable AI systems.","Senior Data Annotation Jobs in Boston",[30,33,36,39,42,45,48,51],{"h2":31,"desc":32},"Job Heading: Senior Data Annotation Jobs in Boston","LinkedIn Job Metadata: Title + Senior Data Annotation Jobs in Boston | Date Posted + 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, QA Evaluation, Prompt Evaluation, Named Entity Recognition, Computer Vision Annotation, Content Safety Labeling, Annotation Guidelines Compliance, Training Data Quality, LLM Evaluation, LLM Training Pipelines | Salary Currency + USD | Salary Min + 63360 | Salary Max + 126720 | Pay Period + YEAR",{"h2":34,"desc":35},"About the Role","You will deliver senior-level data labeling and evaluation across text, image, and multimodal tasks, translating annotation guidelines into consistent outputs that improve downstream model performance. The work includes RLHF ranking, prompt evaluation, QA evaluation, and content safety labeling, with a focus on training data quality and reproducible judgments for LLM training pipelines.",{"h2":37,"desc":38},"What You Will Do","Own complex annotation queues and edge cases; perform RLHF preference ranking and critique labeling; execute named entity recognition and taxonomy tagging for NLP datasets; complete computer vision annotation (bounding boxes, polygons, keypoints) when required; run QA evaluation checks, adjudicate disagreements, and document rationale; improve annotation guidelines compliance with clear feedback to operations and engineering; create gold sets, conduct calibration sessions, and track inter-annotator agreement; surface systematic errors that impact large language model evaluation and model performance improvement.",{"h2":40,"desc":41},"Required Qualifications","Mid-Senior experience in data annotation, data labeling, or model evaluation; demonstrated ability to follow and refine annotation guidelines compliance; strong judgment for RLHF-style preference decisions and prompt evaluation; familiarity with training data quality metrics and QA evaluation workflows; comfort working with ambiguous content safety labeling scenarios; strong written communication for rationale, escalation notes, and audit trails; ability to manage throughput while maintaining high precision and consistency.",{"h2":43,"desc":44},"Preferred Qualifications","Experience with LLM evaluation rubrics, instruction-following grading, and safety policy interpretation; exposure to NLP datasets such as named entity recognition and classification; background in computer vision annotation tools and schema design; familiarity with error analysis, sampling strategies, and active learning concepts; experience partnering with engineering teams on data pipelines and annotation tooling.",{"h2":46,"desc":47},"Tools and Workflows","Annotation platforms and labeling tools; dataset versioning and task routing; rubric-based QA evaluation, spot checks, and gold-set validation; structured feedback loops to improve annotation guidelines compliance; reporting of training data quality issues that affect LLM training pipelines and model performance improvement.",{"h2":49,"desc":50},"Why This Role at Rex.zone","Rex.zone connects remote, full-time annotation talent with AI labs, tech startups, BPOs, and annotation vendors. You will work on real-world large language model evaluation, RLHF, and content safety labeling projects, with clear quality standards and measurable impact on training data quality.",{"h2":52,"desc":53},"How to Apply","Apply through Rex.zone with a concise summary of your annotation background, domains (NLP, computer vision, content safety, LLM training pipelines), and examples of QA evaluation or RLHF work. If you have prior guidelines, calibration, or adjudication experience, include details on how you improved annotation guidelines compliance and model performance improvement outcomes.","AI Data Operations"]