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Data Annotation Spanish Jobs in Missouri (NOW HIRING)

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Data Annotation Spanish information

What is data annotation in Spanish?

Data Annotation in Spanish refers to the process of labeling or tagging data—such as text, audio, or images—in the Spanish language to make it understandable for machine learning models. This work helps train artificial intelligence systems to recognize and process Spanish language content accurately. Data annotators may categorize content, transcribe audio, or highlight specific elements in images or texts. The quality of annotated data directly impacts the performance of language models and other AI applications.

What are some common challenges faced by data annotation specialists working with Spanish language data, and how can they be addressed?

Data Annotation Specialists working with Spanish language data often encounter challenges such as managing regional dialects, idiomatic expressions, and cultural nuances that can affect the accuracy of annotations. To address these challenges, it's important to have a strong understanding of the specific dialect or variant required by the project and to consistently refer to established guidelines or glossaries. Collaboration with team members and regular quality checks help ensure consistency and high-quality output, while ongoing training can keep annotators updated on best practices and new annotation tools.

What are the key skills and qualifications needed to thrive as a data annotation specialist (Spanish), and why are they important?

To thrive as a Data Annotation Specialist (Spanish), you need proficiency in the Spanish language, attention to detail, and a basic understanding of data labeling concepts, often supported by a high school diploma or higher. Familiarity with annotation tools such as Labelbox, Supervisely, or proprietary platforms is typically required, along with knowledge of file management systems. Strong communication, consistency, and the ability to work independently are important soft skills for excelling in this position. These skills ensure accurate, high-quality data labeling that directly impacts the performance of AI and machine learning models.

What is the difference between Data Annotation Spanish vs Data Labeling Specialist?

AspectData Annotation SpanishData Labeling Specialist
CredentialsBasic computer skills, attention to detailSimilar, often requires familiarity with labeling tools
Work EnvironmentRemote or office-based, tech companiesRemote or on-site, tech and AI industries
Industry UsageUsed in AI training for Spanish language dataUsed across various industries for data preparation
Search IntentLooking for Spanish-specific annotation rolesSearching for general data labeling jobs

Data Annotation Spanish focuses on annotating data specifically in Spanish, often requiring language skills. Data Labeling Specialist is a broader role involving labeling data in various formats and languages. Both roles are essential in AI development, but Data Annotation Spanish is specialized for Spanish language datasets.

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What job categories do people searching Data Annotation Spanish jobs in Missouri look for?

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Data Annotation Spanish jobs near you
Infographic showing various Data Annotation Spanish job openings in Missouri as of August 2026, with employment types broken down into 1% As Needed, 87% Full Time, 10% Part Time, and 2% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution.

Phonetician / Linguist (Spanish-US)

Omilia Natural Language Solutions Ltd

California, MO • On-site

$65 - $85/hr

Other

Posted 2 days ago

New

Key responsibilities

  • Conduct systematic phonological and phonetic analysis of the American Spanish language.

  • Build and maintain pronunciation lexicons, including G2P rules and exceptions.

  • Review and correct machine-generated G2P outputs; conduct pronunciation audits.

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 American Spanish language.
  • 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.
  • 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.
  • 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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