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Flexible Remote Image Annotation Jobs in Georgia

This is an hourly paid, fully remote contractor role with flexible work-from-anywhere hours. This ... Prior experience with AI data training, annotation, or evaluation workflows is strongly preferred.

New

Channel Sales Manager

Atlanta, GA · Remote

$146K/yr

Our advanced microscopes and AI-based image analysis solutions enable users to gain profound ... We recognize the benefits of flexible, remote working arrangements for eligible roles and are ...

Medical OEM Territory Manager

Atlanta, GA · On-site +1

$105K - $115K/yr

... image across the target market. * Maintain and continually develop product, market, and technical ... We recognize the benefits of flexible, remote working arrangements for eligible roles and are ...

$94K - $111K/yr

This is a remote role open to any location in continental US Manulife is a leading international ... Project a professional image and serve as an example to junior staff. * Manage all aspects of ...

Define cloud, container, and DevSecOps security standards including image governance, runtime ... and flexible working arrangements. In this role, you can expect: * Remote Work: Enjoy the ...

$223K - $259K/yr

Whether you're in a stadium, airplane, or remote military base, Ditto's peer-to-peer sync engine ... Design and implement flexible network configuration patterns that give customers choice of ingress ...

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Flexible Remote Image Annotation information

What is flexible remote image annotation?

Flexible remote image annotation is a job where individuals label or tag elements within digital images from a remote location, often from home. This work is crucial for training artificial intelligence and machine learning models, particularly in fields like computer vision and autonomous vehicles. The 'flexible' aspect means workers can often set their own hours and choose tasks according to their availability. Image annotation tasks may include outlining objects, assigning categories, or describing visual content in images. Most positions require attention to detail and basic computer skills, but prior experience is not always necessary.

What are the key skills and qualifications needed to thrive as a Flexible Remote Image Annotation Specialist, and why are they important?

To thrive as a Flexible Remote Image Annotation Specialist, you need strong attention to detail, visual accuracy, and a basic understanding of image processing, often supported by a high school diploma or equivalent. Familiarity with annotation tools such as Labelbox, CVAT, or VIA, and sometimes experience with basic data entry platforms, is typically required. Excellent time management, communication skills, and the ability to work independently are valued soft skills for this remote role. These skills ensure high-quality, consistent data labeling essential for training reliable machine learning models and supporting AI development.

What are some common challenges faced in flexible remote image annotation roles and how can they be managed?

One common challenge in flexible remote image annotation is maintaining accuracy and consistency across large datasets, especially when guidelines are complex or images are ambiguous. Working independently can also make it harder to get immediate feedback or clarification. To manage these challenges, it’s important to regularly review annotation guidelines, participate in team check-ins or forums, and make use of quality assurance tools provided by the employer. Staying organized and communicating proactively with project leads can help ensure your work meets expectations and deadlines.

What is the difference between Flexible Remote Image Annotation vs Data Labeler?

AspectFlexible Remote Image AnnotationData Labeler
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentRemote, flexible hoursRemote, flexible hours
Industry UsageAI, machine learning, computer visionAI, machine learning, data processing
Job FocusAnnotating images with labels, bounding boxes, segmentationLabeling data, categorizing images or text

Flexible Remote Image Annotation and Data Labeler roles both involve data processing tasks in AI and machine learning industries. While image annotation focuses on marking specific features within images, data labelers may work with various data types, including text and images. Both roles are remote, require similar skills, and serve the same industry needs, but image annotation emphasizes visual data precision.

What are the most commonly searched types of Remote Image Annotation jobs in Georgia? The most popular types of Remote Image Annotation jobs in Georgia are:
What job categories do people searching Flexible Remote Image Annotation jobs in Georgia look for? The top searched job categories for Flexible Remote Image Annotation jobs in Georgia are:
What cities in Georgia are hiring for Flexible Remote Image Annotation jobs? Cities in Georgia with the most Flexible Remote Image Annotation job openings:

Kannada Linguistic QA Specialist (Remote)

Braintrust

Savannah, GA • Remote

$20 - $30/hr

Full-time

Posted 2 days ago

New


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 Kannada Quality Assurance Lead (QAL) to oversee quality, consistency, and trainer performance across Kannada AI training projects. You will review AI-generated Kannada content and trainer/QA work, evaluate output quality against project guidelines, provide precise written feedback, and ensure that all contributors follow the expected quality 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 Kannada 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 Kannada quality leadership will directly help improve the world’s premier AI models by ensuring that Kannada training data is natural, accurate, culturally appropriate, well-documented, and aligned with client expectations.

Your profile
  • Bachelor’s or Master’s degree in Kannada, Linguistics, Translation, Communications, Journalism, English, Education, Quality Assurance, or a relevant domain/related field.
  • Native or near-native Kannada 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 Kannada writing, editing, translation, localization, content QA, AI training, education, annotation, or related language-review workflows.
  • Strong understanding of Kannada grammar, spelling conventions, punctuation, tone, register, regional variation, and cultural context.
  • Ability to evaluate Kannada 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 Kannada 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 Kannada wording, register, translation fidelity, cultural context, regional variation, 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 Kannada 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 Kannada-specific style requirements.
  • Quality alignment: Ensure all trainers and QAs apply Kannada 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 Kannada-language projects.