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Data Annotation Jobs in Quebec (NOW HIRING)

Skadra

Spécialiste en vision

Quebec, QC · On-site

Mettre en place des processus de collecte, annotation, nettoyage, augmentation et validation de données d'images. * Intégration logicielle : Intégrer les algorithmes dans des applications ...

Skadra

Spécialiste en vision

Quebec, QC

Mettre en place des processus de collecte, annotation, nettoyage, augmentation et validation de données d'images. Intégration logicielle : Intégrer les algorithmes dans des applications ...

hireVouch

Forward Deployed Engineer

Quebec, QC

... Support data collection and annotation efforts at customer sites when needed What We Are Looking For​ Must-Haves • 6+ years of experience combining production software engineering with ...

All JobsData Annotation JobsData Annotation Jobs in Quebec

Data Annotation information

See Quebec salary details

$9

$25

$54

How much do data annotation jobs pay per hour?

As of Jul 15, 2026, the average hourly pay for data annotation in Quebec is $25.23, according to ZipRecruiter salary data. Most workers in this role earn between $17.07 and $30.05 per hour, depending on experience, location, and employer.

What does a typical workday look like for someone in a Data Annotation role?

A typical workday as a Data Annotator involves reviewing datasets—such as images, audio, text, or video—and accurately labeling or categorizing information according to specific project guidelines. Most Data Annotators work independently, but they often collaborate with project managers or data scientists to clarify requirements and resolve ambiguities. Tasks may be repetitive, but adhering to precise standards is vital for maintaining data quality. Work environments can range from technology companies to remote or freelance settings, and advancement opportunities exist as team leads or quality assurance specialists for those who excel in consistency and reliability.

Is data annotation a genuine job?

Data annotation is a legitimate job that involves labeling data such as images, text, or audio to help train machine learning models. It often requires attention to detail and familiarity with annotation tools, and can be found in various industries like technology and healthcare.

Does data annotation pay well?

Data annotation jobs typically offer entry-level pay that varies depending on the employer, location, and complexity of the tasks. While some positions pay hourly wages comparable to other administrative or clerical roles, experienced annotators working on specialized projects or with advanced tools can earn higher rates. Overall, data annotation is often considered an entry-level position with moderate pay potential.

What is a Data Annotation job?

A Data Annotation job involves labeling and categorizing data, such as text, images, audio, or video, to help train machine learning models. Annotators apply tags, bounding boxes, or classifications to data based on specific guidelines. This process improves the accuracy of AI systems in recognizing patterns and making predictions. Many data annotation jobs require attention to detail and familiarity with specific domains. It is commonly used in applications like autonomous driving, natural language processing, and computer vision.

How hard is it to get hired by data annotation?

Getting hired for a data annotation role generally requires basic computer skills, attention to detail, and sometimes familiarity with specific tools or platforms. Many positions are entry-level and do not require advanced education, making the hiring process relatively accessible, though competition can vary based on the employer and location.

What are the key skills and qualifications needed to thrive in the Data Annotation position, and why are they important?

To thrive in Data Annotation, you need strong attention to detail, accuracy, and basic data handling skills, often supported by a high school diploma or equivalent. Familiarity with annotation platforms, data labeling software, or content management systems is frequently required, though specific certifications are rare. Excellent communication, time management, and the ability to focus on repetitive tasks distinguish top performers in this role. These skills are crucial because accurate and consistent data annotation directly impacts the quality of machine learning models and AI applications.

What does a data annotator do?

A data annotator labels and tags data such as images, text, or videos to help machine learning models understand and learn from the data. They use tools and follow guidelines to ensure accuracy and consistency, often working with large datasets in a structured environment. Attention to detail and knowledge of annotation tools are important for this role.
What job categories do people searching Data Annotation jobs in Quebec look for? The top searched job categories for Data Annotation jobs in Quebec are:
Data Annotation jobs near you
Infographic showing various Data Annotation job openings in Quebec as of July 2026, with employment types broken down into 85% Full Time, and 15% Contract. Highlights an 69% In-person, 10% Hybrid, and 21% Remote job distribution, with an average salary of $52,488 per year, or $25.2 per hour.

Phonetician / Linguist (fr-CA & en-CA)

Omilia

Quebec, QC • On-site

Other

PTO

Re-posted 16 days ago

Job description

Role Purpose

Ensure the linguistic and phonetic quality of Omilia's multilingual Text-to-Speech (TTS) systems by designing phoneme inventories, developing lexicons, and reviewing audio corpora to support enterprise-grade voice experiences.

Accountabilities
  • Autonomy: Independently conduct phonological and phonetic analysis, design phoneme inventories, and develop lexicons for multiple languages.
  • Scope & Complexity: Responsible for linguistic quality across all supported languages in TTS, including handling underrepresented phenomena and complex language-specific features.
  • Impact: Directly influences the naturalness, accuracy, and quality of Omilia's TTS output, impacting customer experience in global contact center deployments.
  • Influence/Mentorship: Collaborates with TTS engineers, data scientists, and ML researchers; coordinates with native-speaker reviewers and external annotation pipelines.
Key Responsibilities
  • Conduct systematic phonological and phonetic analysis of the Canadian French and Canadian English languages.
  • Document language-specific features (prosody, stress, tone, coarticulation, dialect variation).
  • Produce structured language profiles for TTS model training and evaluation.
  • Define and maintain phoneme inventories; map to IPA and TTS-specific conventions.
  • Corpus audits and optimal audio references selections for TTS target voice tuning
  • Build and maintain pronunciation lexicons, including G2P rules and exceptions.
  • Review and correct machine-generated G2P outputs; conduct pronunciation audits.
  • Annotate audio corpora, develop evaluation protocols, and produce error analyses.
  • Define linguistic criteria for TTS corpus selection and design prompts for data collection.
  • Collaborate with TTS engineers to integrate linguistic artefacts into synthesis pipelines.
  • Contribute to internal documentation and participate in research discussions.

Requirements

  • M.Sc. or Ph.D. in Linguistics, Phonetics, Computational Linguistics, or related field.
  • Proven experience building pronunciation lexicons or G2P systems for TTS or ASR.
  • Deep knowledge of phonological theory, articulatory and acoustic phonetics.
  • Proficiency with IPA and at least one machine-readable phoneme notation system (X-SAMPA, ARPAbet, etc.).
  • Experience with corpus annotation tools (Praat, ELAN, WebAnno, etc.).
  • Strong analytical and documentation skills.
  • Fluency in English; proficiency in at least one additional language relevant to Omilia's markets.
  • Technical skills: Praat, ELAN, Audacity, PLS/CMUdict/SSML lexicon formats, Phonetisaurus/Sequitur/neural G2P, basic Python or shell scripting, TTS text normalization.

Benefits

  • Fixed compensation;
  • Long-term employment with the working days vacation;
  • Development in professional growth (courses, training, etc);
  • Being part of successful cutting-edge technology products that are making a global impact in the service industry;
  • Proficient and fun-to-work-with colleagues;
  • Apple gear.

Omilia is proud to be an equal opportunity employer and is dedicated to fostering a diverse and inclusive workplace. We believe that embracing diversity in all its forms enriches our workplace and drives our collective success. We are committed to creating an environment where everyone feels welcomed, valued, and empowered to contribute their unique perspectives without regard to factors such as race, color, religion, gender, gender identity or expression, sexual orientation, national origin, heredity, disability, age, or veteran status, all eligible candidates will be given consideration for employment.

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