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Day Shift Remote Data Annotation Jobs in Texas (NOW HIRING)

$14 - $18/hr

Pay $11.25 Monolingual, $11.75 bilingual Weekly Pay & Benefits Day Shift, Remote Member Service Representatives, Enrollment Reps, and Credentialing needed for customer inquiries regarding enrollment ...

Showing results 21-40

Day Shift Remote Data Annotation information

What are the key skills and qualifications needed to thrive as a day shift remote data annotation specialist?

To excel as a Day Shift Remote Data Annotation Specialist, strong attention to detail, a solid understanding of data labeling concepts, and basic computer literacy are essential, often supported by a high school diploma or equivalent. Familiarity with annotation platforms, data management tools, and sometimes knowledge of specific industry standards or guidelines is typically expected. Excellent time management, communication skills, and the ability to work independently make candidates stand out in this remote role. These capabilities ensure accuracy, efficiency, and reliability in processing and labeling data, which are critical for the quality of machine learning and AI projects.

What is the difference between Day Shift Remote Data Annotation vs Day Shift Remote Data Labeling?

AspectDay Shift Remote Data AnnotationDay Shift Remote Data Labeling
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentRemote, computer-basedRemote, computer-based
Industry UsageTech, AI, Machine LearningTech, AI, Machine Learning
Job FocusAdding annotations to datasetsApplying labels to datasets

Both roles involve working remotely in tech and AI industries, requiring similar skills. Data annotation typically involves marking specific features in data, while data labeling focuses on assigning categories. The main difference lies in the terminology and specific task details, but both are essential for training AI models.

What are some common challenges faced by remote data annotation professionals working day shifts, and how can they be managed?

Remote data annotation professionals on day shifts often encounter challenges such as staying focused during repetitive tasks, maintaining high accuracy, and managing communication across distributed teams. To address these, it's helpful to establish a structured daily routine, take regular short breaks to reduce eye strain and fatigue, and use productivity tools to track progress. Proactive communication with team members and supervisors—using chat platforms or regular video check-ins—also helps ensure alignment on project guidelines and fosters a collaborative remote work environment.

What is a day shift remote data annotation?

A Day Shift Remote Data Annotation job involves labeling or tagging data—such as images, text, audio, or video—so that it can be used to train machine learning models. This work is performed remotely, generally during regular daytime business hours. Data annotators follow specific guidelines to ensure accuracy and consistency, making their work crucial for the development of artificial intelligence systems. Some common tasks include identifying objects in images or transcribing spoken words in audio files. The role typically requires attention to detail and basic computer skills, but extensive technical expertise is usually not required.
What are the most commonly searched types of Shift Remote Data Annotation jobs in Texas? The most popular types of Shift Remote Data Annotation jobs in Texas are:
What are popular job titles related to Day Shift Remote Data Annotation jobs in Texas? For Day Shift Remote Data Annotation jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Day Shift Remote Data Annotation jobs in Texas look for? The top searched job categories for Day Shift Remote Data Annotation jobs in Texas are:
What cities in Texas are hiring for Day Shift Remote Data Annotation jobs? Cities in Texas with the most Day Shift Remote Data Annotation job openings:
Infographic showing various Day Shift Remote Data Annotation job openings in Texas as of June 2026, with employment types broken down into 80% Full Time, 16% Part Time, 2% Temporary, and 2% Contract. Highlights an 100% Remote job distribution.

Gujarati Linguistic QA Specialist (Remote)

Braintrust

Austin, TX • Remote

$20 - $30/hr

Full-time

This job post has expired 1 day ago. Applications are no longer accepted.


Job description

Company
Braintrust is a global talent network that connects top independent professionals with leading companies for high-quality, flexible work. We help organizations hire skilled talent faster while giving professionals access to vetted opportunities with innovative teams. Job description
About this role

In this hourly, remote contractor role, you will work as a Gujarati Quality Assurance Lead (QAL) to oversee quality, consistency, and trainer performance across Gujarati AI training projects. You will review AI-generated Gujarati content and trainer/QA work, evaluate output quality against project guidelines, provide precise written feedback, and help ensure that all contributors follow the expected standards.
You will assess work for accuracy, fluency, grammar, spelling, tone, cultural appropriateness, meaning preservation, instruction-following, formatting, and adherence to project-specific rubrics. You will spot recurring quality issues, communicate updates to trainers and QAs, support onboarding, maintain documentation, and help activate contributors who are not working consistently. This role requires strong Gujarati and English skills, excellent attention to detail, structured communication, and the ability to manage quality workflows across remote teams.
This role is with SME Careers, a fast-growing AI Data Services company and subsidiary of SuperAnnotate, delivering training data for many of the world’s largest AI companies and foundation-model labs. Your Gujarati quality leadership will directly help improve the world’s premier AI models by ensuring that Gujarati training data is natural, accurate, culturally appropriate, well-documented, and aligned with client expectations.
Selection process involves an AI interview, a domain-specific task, and an interview with a recruiter.

Your profile
  • Bachelor’s or Master’s degree in Gujarati, Linguistics, Translation, Communications, Journalism, English, Education, Quality Assurance, or a relevant domain/related field.
  • Native or near-native Gujarati proficiency with strong reading and writing skills.
  • Strong grasp of the English language to follow project guidelines, communicate with teams, and provide clear feedback in English.
  • 3+ years of professional experience in Gujarati writing, editing, translation, localization, content QA, AI training, education, annotation, or related language-review workflows.
  • Strong understanding of Gujarati grammar, spelling conventions, punctuation, tone, register, and cultural context.
  • Ability to evaluate Gujarati content against detailed rubrics and identify issues such as mistranslation, literal phrasing, unnatural tone, hallucinated claims, ambiguity, or inconsistent terminology.
  • Experience leading or supporting remote teams of trainers, annotators, reviewers, editors, or QAs is strongly preferred.
  • Comfortable working in fast-moving remote environments using tools such as Discord, Google Sheets, Google Docs, trackers, dashboards, and project management systems.
  • Highly detail-oriented and organized, with the ability to maintain style guides, FAQs, trackers, onboarding materials, honeypots, and other quality documentation.
  • Experience with AI training, data annotation, large language models, prompt/response evaluation, or rubric-based LLM QA is a strong plus.
Key responsibilities
  • Quality monitoring: Spot-check Gujarati items, identify quality issues, provide ongoing feedback through DMs, and escalate recurring or critical issues.
  • Trainer and QA communication: Update trainers and QAs on Discord about new item guidelines, project changes, workflow updates, and quality expectations.
  • Question handling: Respond to trainer/QA questions clearly and promptly, especially around Gujarati wording, register, translation fidelity, cultural context, and edge cases.
  • Trainer/QA activation management: DM contributors who are inactive or not working, encourage activation, track follow-ups, and flag availability issues when needed.
  • Documentation: Create and maintain Gujarati project documentation, including style guides, trackers, FAQs, quality notes, examples, honeypots, and onboarding materials.
  • Onboarding and training: Schedule and run onboarding/training calls with trainers and QAs to explain project expectations, workflows, rubrics, quality standards, and Gujarati-specific style requirements.
  • Quality alignment: Ensure all trainers and QAs apply Gujarati language guidelines consistently and understand updates as projects evolve.
  • Process improvement: Identify recurring quality gaps, propose workflow improvements, and help build scalable QA processes for Gujarati-language projects.