Remote Data Annotation Jobs in Vancouver

About The Role Support AI/ML training pipelines by performing remote data annotation and evaluation across NLP, computer vision, and content safety. You will label and review datasets, complete RLHF preference ranking, and deliver rubric-based prompt and QA evaluations to improve training data quality and model performance. What You Will Do Execute data labeling for text, image, and multimodal tasks using web-based tools Perform named entity recognition (NER), text classification, and span labeling as required Complete RLHF pairwise comparisons and preference ranking with clear rationale notes Run prompt evaluation using rubrics for helpfulness, correctness, and safety Conduct QA evaluation, sampling, and audits to ensure guideline compliance and consistency Annotate computer vision data (bounding boxes, polygons, segmentation masks) when assigned Perform content safety labeling for sensitive or policy-violating material when needed Document edge cases, track disagreements, and propose guideline clarifications Collaborate asynchronously with distributed teams to meet throughput and quality targets Required Qualifications Experience with professional data annotation, data labeling, or evaluation workflows Strong written English for rubric-based judgments and structured feedback Ability to follow detailed annotation guidelines and maintain consistency under QA review Familiarity with NLP concepts (classification, NER) and/or computer vision annotation fundamentals Comfort working with online labeling tools, spreadsheets, and documentation Reliable remote work setup and availability for full-time schedules Preferred Qualifications Hands-on experience with RLHF evaluation, prompt evaluation, or LLM output grading Experience conducting QA evaluation, calibration sessions, or inter-annotator agreement checks Understanding of LLM failure modes (hallucinations, prompt injection, unsafe outputs) Exposure to taxonomy/ontology or guideline authoring Compensation Hourly pay range: $30–$50 USD (HOURLY), based on task complexity, performance, and project needs. How To Apply Apply via Rex.zone and include your annotation experience plus examples of RLHF, prompt evaluation, and QA evaluation work that demonstrates strong guideline adherence and training data quality focus.

Support AI/ML training pipelines by performing data annotation, RLHF preference ranking, and rubric-based evaluations across NLP and computer vision. Responsibilities include labeling datasets, conducting QA audits, and documenting edge cases to improve model performance.

Requires professional experience in data annotation workflows and strong written English for structured feedback. Candidates must be familiar with NLP or computer vision fundamentals and possess a reliable remote work setup for full-time schedules.

Relevées dans la description du poste. Confirmez les exigences importantes ci-dessus.

• Data Annotation
• RLHF
• NLP
• Computer Vision
• Named Entity Recognition
• Text Classification
• Prompt Evaluation
• QA Evaluation
• Content Safety Labeling
• Data Labeling
• Multimodal Tasks
• Span Labeling

• Data & Analytics
• Technology
• Software
• Science & Research
• Engineering

Expérience minimale

2+ ans

Postuler avant le

29 août 2026

Langue de l’offre

anglais

Heures de travail

40 heures par semaine

Exigences de lieu

Country, Vancouver, British Columbia, Canada

Niveau d’expérience

Mid-Senior level