Senior Data Labeling Specialist (Vancouver)

Senior Data Labeling Specialist (Vancouver) — Remote (Full-Time) Senior data labeling roles power AI/ML training workflows by producing high-quality training data for LLMs and computer vision models through data annotation, RLHF preference ranking, QA evaluation, and guideline-driven review across real production pipelines. About The Role You will lead and execute senior-level data labeling and review work that improves model performance for large language models and vision systems. You will annotate and audit datasets, run QA evaluation against annotation guidelines, perform RLHF preference ranking for response quality, and deliver structured feedback to improve training data quality. Work includes prompt evaluation, named entity recognition, content safety labeling, and computer vision annotation (bounding boxes, polygons, segmentation) depending on project needs. What You Will Do Own end-to-end labeling execution, quality auditing, and escalation handling for ambiguous edge cases in NLP and CV tasks Apply taxonomy definitions, maintain decision logs, and measure inter-annotator agreement Support RLHF and evaluation pipelines by ranking outputs, identifying failure modes, and tagging safety/policy violations Help define gold-standard sets, build rubrics for QA evaluation, and improve guideline compliance across distributed teams Collaborate with engineers and model stakeholders to resolve ambiguity and calibrate decisions Requirements Strong experience in data labeling/data annotation with documented QA evaluation responsibility Ability to interpret complex annotation guidelines and apply consistent judgment at high throughput Familiarity with RLHF, prompt evaluation, named entity recognition, computer vision annotation, and content safety labeling Comfort working independently in a remote environment and communicating edge cases clearly How To Apply Apply via Rex.zone and include examples of guideline interpretation, QA outcomes, and any RLHF or prompt evaluation work. Highlight domains (NLP, computer vision, content safety) and any metrics (agreement rates, defect reductions, throughput vs. quality targets).

Lead and execute senior-level data labeling, auditing, and RLHF preference ranking to improve LLM and computer vision model performance. Collaborate with engineers to resolve ambiguity, define gold-standard sets, and maintain quality rubrics.

Requires strong experience in data labeling and QA evaluation with the ability to interpret complex guidelines. Familiarity with RLHF, NLP, and computer vision annotation is essential for success in this remote role.

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

• Data Labeling
• Data Annotation
• RLHF
• QA Evaluation
• NLP
• Computer Vision
• Named Entity Recognition
• Content Safety Labeling
• Prompt Evaluation
• Bounding Boxes
• Polygons
• Segmentation
• Taxonomy Definition
• Inter-annotator Agreement
• Guideline Interpretation
• Audit Datasets

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

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