Senior Data Labeling Jobs in Montreal

Senior Data Labeling roles at Rex.zone focus on training data quality for modern AI systems. You will apply expert data labeling, RLHF evaluation, prompt evaluation, and QA evaluation to improve large language model evaluation and computer vision annotation outcomes. This remote, full-time role supports LLM training pipelines by enforcing annotation guidelines compliance, resolving edge cases, and driving model performance improvement through consistent labeling operations. If you are seeking senior data labeling jobs in Montreal with remote flexibility, you will work with multilingual datasets, content safety labeling, and structured tasks such as named entity recognition, intent classification, and image/video bounding boxes for NLP and CV.

Senior Data Labeling Jobs in Montreal — LinkedIn Job Metadata

About the Role

As a Senior Data Labeling Specialist, you will execute and improve labeling workflows used to train and evaluate NLP and computer vision models. Your work will include RLHF-style preference ranking, prompt-response evaluation, and systematic QA evaluation to ensure high training data quality. You will interpret annotation guidelines, handle ambiguous edge cases, and partner with leads to refine taxonomies so labels remain consistent across annotators and over time.

What You Will Do

You will label and review complex datasets for LLM training pipelines including dialogue, instruction-following, and content safety labeling; perform RLHF evaluation tasks such as ranking, pairwise preference judgments, and rubric-based scoring; run QA evaluation to audit inter-annotator agreement, fix systematic errors, and enforce annotation guidelines compliance; complete NLP tasks such as named entity recognition, sentiment/intent classification, and text span annotations; support computer vision annotation including bounding boxes, polygons, keypoints, segmentation masks, and video frame review; document edge cases, propose guideline updates, and help maintain a high-signal dataset that drives model performance improvement.

Required Qualifications

You have experience in data labeling or data annotation operations with strong quality ownership; you can apply detailed rubrics and follow annotation guidelines compliance standards; you are comfortable evaluating LLM outputs using consistent scoring criteria for helpfulness, harmlessness, and policy adherence; you can reason about ambiguity and justify labeling decisions clearly; you can work independently in a remote setting while meeting throughput and accuracy targets.

Preferred Qualifications

You have experience with RLHF, prompt evaluation, and large language model evaluation; you have exposure to content safety labeling, policy interpretation, and escalation workflows; you have worked on NLP datasets such as named entity recognition or multilingual classification; you have contributed to computer vision annotation projects and understand common CV failure modes; you have experience reviewing other annotators’ work, improving QA evaluation processes, or optimizing labeling operations.

Tools, Data Types, and Workflows

You will work with annotation tooling for text, image, and video tasks, apply structured rubrics for evaluation, and follow versioned guidelines. Common workflows include gold set calibration, blind review, sampling-based QA, adjudication, error taxonomy tracking, and iterative guideline refinement. Data types may include chat transcripts, prompts and completions, short-form and long-form text, entity spans, and visual assets requiring bounding boxes or segmentation.

Why This Role at Rex.zone

Rex.zone connects skilled contributors to high-impact labeling and evaluation work supporting AI labs, tech startups, and annotation vendors. These senior data labeling jobs in Montreal (remote) are designed for professionals who want stable full-time work while contributing to real-world AI/ML training workflows across NLP, computer vision, and content safety.

How to Apply

Apply through Rex.zone and complete the role-relevant screening tasks. Your evaluation may include annotation guideline interpretation, QA evaluation scenarios, and short RLHF or prompt evaluation exercises to confirm accuracy, consistency, and judgment.

Frequently Asked Questions

Q: Are these senior data labeling jobs in Montreal remote?
Yes. The role is explicitly Remote and designed to be performed from a home office while collaborating with distributed teams.
Q: What does “senior data labeling” mean in practice?
It means handling complex labeling and evaluation tasks, resolving edge cases, improving annotation guidelines compliance, and contributing to QA evaluation processes that increase training data quality.
Q: Will I work on RLHF and large language model evaluation?
Yes. Tasks may include RLHF evaluation, preference ranking, rubric-based scoring, and prompt evaluation to support LLM training pipelines and model performance improvement.
Q: What domains are included: NLP, computer vision, or content safety?
Depending on project needs, you may work across NLP (including named entity recognition), computer vision annotation (boxes/segmentation), and content safety labeling for policy-aligned datasets.
Q: Is this a contract, freelance, or full-time position?
This posting is for FULL_TIME employment. Rex.zone may also list contract or freelance roles separately, but this job is full-time and remote.
Q: What makes candidates successful in this role?
Consistent judgment, careful reading of rubrics, high accuracy under QA evaluation, clear documentation of edge cases, and the ability to maintain annotation guidelines compliance while meeting throughput targets.

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