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Annotation Labelling Jobs in Clermont, FL (NOW HIRING)

... labeling/annotation; - Strong analytical skills, exceptional attention to detail, and sharp pattern recognition abilities; - Proven experience reviewing, processing, and navigating high-volume ...

Annotation Labelling information

What is annotation labelling?

Annotation labelling is the process of tagging or marking data—such as images, text, or audio—with relevant information or labels. This is an essential step in preparing datasets for machine learning and artificial intelligence models, as it helps algorithms understand and learn from raw data. Annotation labelling can include tasks like identifying objects in photos, transcribing speech, or categorizing text. Skilled annotators ensure accuracy and consistency to improve model performance. People in this role often use specialized tools or software to streamline and standardize the annotation process.

What are the key skills and qualifications needed to thrive as an Annotation Labelling Specialist, and why are they important?

To thrive as an Annotation Labelling Specialist, you need strong attention to detail, data analysis capabilities, and familiarity with data annotation standards, usually supported by a background in computer science or related fields. Proficiency with annotation tools such as Labelbox, CVAT, or Supervisely, and sometimes knowledge of basic programming or scripting, is typically required. Excellent communication, consistency, and the ability to follow complex instructions are crucial soft skills for producing high-quality labeled data. These skills ensure the accuracy and reliability of datasets, which are foundational for successful machine learning and AI model development.

What are some common challenges faced by Annotation Labelling professionals, and how can they be managed?

Annotation Labelling professionals often encounter challenges such as maintaining high accuracy while handling repetitive data, meeting tight deadlines, and adapting to evolving project guidelines. To manage these, it’s important to develop strong attention to detail, regularly communicate with team leads to clarify instructions, and leverage annotation tools efficiently. Collaborating closely with quality assurance teams can also help identify and correct errors early, ensuring consistently high-quality outputs.

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

AspectAnnotation LabellingData Labeling Specialist
CredentialsBasic technical skills, attention to detailSimilar skills, sometimes additional domain knowledge
Work EnvironmentData annotation platforms, remote or officeData annotation tasks, often remote or in-office
Industry UsageAI, machine learning, autonomous vehiclesAI, machine learning, healthcare, retail
Search & ComparisonCommonly compared for entry-level data tasksRelated but broader role

Annotation Labelling involves marking data such as images, text, or videos to train AI models. Data Labeling Specialists perform similar tasks but may have a broader scope, including verifying and managing labeled data. Both roles are essential in AI development, often overlapping in skills and work environment, but Annotation Labelling is more focused on the annotation process itself.

What cities near Clermont, FL are hiring for Annotation Labelling jobs? Cities near Clermont, FL with the most Annotation Labelling job openings:
Taxonomy Analyst ID76178

Taxonomy Analyst ID76178

AgileEngine

Orlando, FL • On-site

Full-time

Posted 20 days ago


Job description


AgileEngine is an Inc. 5000 company that creates award-winning software for Fortune 500 brands and trailblazing startups across 17+ industries. We rank among the leaders in areas like application development and AI/ML, and our people-first culture has earned us multiple Best Place to Work awards.
WHY JOIN US
If you're looking for a place to grow, make an impact, and work with people who care, we'd love to meet you!
ABOUT THE ROLE
We are looking for a Taxonomy Analyst with native-level English fluency to review, annotate, and classify large-scale job and resume datasets according to strict taxonomy guidelines for an HR tech platform serving global English-speaking markets. You will standardize job titles, map occupations, validate metadata, and perform data cleanup across high-volume datasets while adapting content for regional relevance across diverse English markets. The role requires exceptional pattern recognition, attention to detail, and sound independent judgment on ambiguous data points.
WHAT YOU WILL DO
- Review, annotate, and classify large-scale datasets (job descriptions, resumes, and skill profiles) according to strict taxonomy guidelines;
- Support daily operations by standardizing job titles, mapping occupations, validating metadata, and continuously improving overall taxonomy quality;
- Perform data cleanup and validation to identify patterns, resolve inconsistencies, and ensure accurate, standardized outputs;
- Adapt and validate multilingual and localized content to ensure regional relevance across diverse English markets;
- Strictly follow established labeling guidelines while exercising sound, independent judgment on ambiguous data points.
MUST HAVES
- You must be authorized to work for ANY employer in the US (e.g., Green card holders, TN visa holders, GC EAD, H4 EAD, U4U with EAD), as we are unable to sponsor or take over employment visa sponsorship at this time;
- Native-level fluency in English;
- 3+ years of proven experience in taxonomy, metadata management, content classification, data validation, or data labeling/annotation;
- Strong analytical skills, exceptional attention to detail, and sharp pattern recognition abilities;
- Proven experience reviewing, processing, and navigating high-volume datasets.
NICE TO HAVES
- Market knowledge or familiarity with the professional landscapes of Ireland, India, the United Arab Emirates, Australia, or Singapore;
- Domain knowledge in HR tech, recruitment, or job taxonomy (occupational mapping, labor market structures);
- Proficiency with Excel / Google Sheets or basic SQL queries;
- Hands-on experience working with LLMs / AI tools (e.g., ChatGPT, Gemini, Claude) for data curation or evaluation.
PERKS AND BENEFITS
- Professional growth: Mentorship, TechTalks, and personalized growth roadmaps.
- Competitive compensation: USD-based pay with education, fitness, and team activity budgets.
- Exciting projects: Modern solutions with Fortune 500 and top product companies.
- Flextime: Flexible schedule with remote and office options.