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Data Labeling Jobs in Virginia (NOW HIRING)

AgileEngine

Taxonomy Analyst

Richmond, VA · On-site

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 ...

Govcio LLC

Senior Application Developer

Fairfax, VA · On-site

$135K - $165K/yr

Familiarity with cross-domain solution architectures, data labeling, and secure data transfer protocols. * Experience working in secure environments, preferably within the DOJ, and understanding of ...

Govcio LLC

Senior Application Developer

Fairfax, VA · On-site

$135K - $165K/yr

Familiarity with cross-domain solution architectures, data labeling, and secure data transfer protocols. * Experience working in secure environments, preferably within the DOJ, and understanding of ...

SOSi

Machine Learning Engineer- Senior

Chantilly, VA · On-site

$125K - $165K/yr

Understanding of how to craft prompts for discrete tasks such as data labeling and processing. * Experience with asynchronous Python development using frameworks like Ray and FastAPI. * Experience ...

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Data Labeling information

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

To thrive in Data Labeling, you need meticulous attention to detail, strong analytical abilities, and basic computer literacy, often supported by a high school diploma or equivalent. Familiarity with data annotation tools, image or text editing software, and experience with platforms like Labelbox or Amazon SageMaker Ground Truth are commonly advantageous. Exceptional concentration, patience, and the ability to follow precise instructions are valuable soft skills in this position. These skills and qualities are essential for ensuring the accuracy and consistency of labeled datasets, which are critical for training reliable AI and machine learning models.

What is a Data Labeling job?

A Data Labeling job involves annotating or tagging data, such as images, text, audio, or videos, to help train machine learning models. Labelers follow specific guidelines to classify data accurately so that AI systems can learn patterns and make predictions. This role is essential in fields like computer vision, natural language processing, and speech recognition. Strong attention to detail and consistency are crucial for ensuring high-quality training datasets.

What are the typical day-to-day responsibilities of a Data Labeling professional?

A Data Labeling professional is primarily responsible for reviewing and accurately tagging images, text, audio, or video data according to specified guidelines. Daily tasks often include managing large datasets, using annotation software to classify data, and verifying the quality and accuracy of the labels. Collaboration with data scientists, project managers, and other annotators is common, especially when clarifying labeling guidelines or resolving ambiguities. Attention to detail is crucial, as high-quality labeled data directly impacts the effectiveness of machine learning models and AI applications. Most positions are structured in team environments, where productivity and communication skills help ensure project deadlines are met.

What is the job description of data labeling?

Data labeling involves annotating or tagging data such as images, text, or videos to help machine learning models understand and learn from the data. The role requires attention to detail, familiarity with labeling tools, and adherence to guidelines to ensure high-quality annotations. It is often performed remotely and may involve repetitive tasks with flexible schedules.

How much are data labelers paid?

Data labelers typically earn between $10 and $20 per hour, depending on experience, location, and the complexity of the labeling tasks. Many positions are freelance or remote, with pay rates varying across platforms and employers.

How do I become a data labeler?

To become a data labeler, you typically need basic computer skills, attention to detail, and the ability to follow instructions. Many positions require no formal degree and offer flexible, part-time schedules; familiarity with data annotation tools or platforms is often helpful. Applying through online job boards or company websites is common for entry-level roles.

Is data labelling a good career?

Data labeling is a common entry-level role in data annotation and machine learning workflows, often requiring attention to detail and basic computer skills. It can provide opportunities to develop skills in data management and AI, but typically offers lower pay and limited advancement without additional training or experience.
What are the most commonly searched types of Data Labeling jobs in Virginia? The most popular types of Data Labeling jobs in Virginia are:
What are popular job titles related to Data Labeling jobs in Virginia? For Data Labeling jobs in Virginia, the most frequently searched job titles are:
What job categories do people searching Data Labeling jobs in Virginia look for? The top searched job categories for Data Labeling jobs in Virginia are:
What cities in Virginia are hiring for Data Labeling jobs? Cities in Virginia with the most Data Labeling job openings:
Data Labeling jobs near you
Infographic showing various Data Labeling job openings in Virginia as of July 2026, with employment types broken down into 1% As Needed, 83% Full Time, 13% Part Time, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.
Taxonomy Analyst (Swedish fluency)

Taxonomy Analyst (Swedish fluency)

AgileEngine

Richmond, VA • On-site

Other

Posted 4 days ago

Job description

Job Title: Taxonomy Analyst

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. 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 Swedish fluency to review, annotate, and classify high-volume job and resume datasets according to strict taxonomy guidelines for an HR tech platform. You will standardize job titles, map occupations, validate metadata, and perform data quality checks while adapting content for cultural and linguistic relevance across the Swedish market. The role requires exceptional pattern recognition, deep knowledge of Sweden's professional landscape, and sound independent judgment on ambiguous data points.

WHAT YOU WILL DO

- Review, annotate, and classify high-volume datasets (job descriptions, resumes, and candidate profiles) according to strict taxonomy guidelines; - Support taxonomy operations by standardizing job titles, mapping occupations, and validating metadata to ensure consistent and accurate outputs; - Perform regular data quality checks, identify language/data patterns, and clean up unstructured data; - Adapt and validate multilingual content, ensuring cultural, linguistic, and market relevance for Sweden; - Strictly follow established labeling guidelines while exercising sound, independent judgment when dealing with ambiguous data.

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 Swedish is mandatory; - Strong professional communication skills in English (written and spoken) for daily syncs, Slack, and written data feedback; - 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 and processing high-volume datasets.

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.

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