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Data Labeler Jobs in Reston, VA (NOW HIRING)

Steampunk

Data Scientist (Generative AI)

Mclean, VA

$125K - $160K/yr

We are looking for a more than just a "Data Scientist", but a technologist with excellent ... Identify, clean, label, and synthesize high-quality datasets for model training, fine-tuning, or ...

Steampunk

Data Scientist (Generative AI)

Mclean, VA

$125K - $160K/yr

We are looking for seasoned Data Scientist (Generative) to work with our existing team of Data ... Identify, clean, label, and synthesize high-quality datasets for model training, fine-tuning, or ...

Steampunk

Data Scientist (Generative AI)

Mclean, VA · On-site +1

$125K - $160K/yr

Overview We are looking for seasoned Data Scientist to work with our existing team of Data ... Identify, clean, label, and synthesize high-quality datasets for model training, fine-tuning, or ...

Steampunk

Data Scientist (Generative AI)

Mclean, VA · On-site

$125K - $160K/yr

We are looking for a more than just a "Data Scientist", but a technologist with excellent ... Identify, clean, label, and synthesize high-quality datasets for model training, fine-tuning, or ...

Steampunk

Data Scientist (Generative AI)

Mclean, VA

$125K - $160K/yr

Overview We are looking for seasoned Data Scientist to work with our existing team of Data ... Identify, clean, label, and synthesize high-quality datasets for model training, fine-tuning, or ...

Steampunk

Data Scientist (Generative AI)

Mclean, VA

$125K - $160K/yr

We are looking for a more than just a "Data Scientist", but a technologist with excellent ... Identify, clean, label, and synthesize high-quality datasets for model training, fine-tuning, or ...

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How much do data labeler jobs pay per hour?

As of May 31, 2026, the average hourly pay for data labeler in Reston, VA is $14.53, according to ZipRecruiter salary data. Most workers in this role earn between $12.98 and $16.01 per hour, depending on experience, location, and employer.

What is a Data Labeler job?

A Data Labeler is responsible for annotating and categorizing data, such as images, text, audio, or video, to train machine learning models. This involves tasks like adding tags, marking objects, or verifying data accuracy based on specific guidelines. Their work is essential for improving AI models in areas like speech recognition, computer vision, and natural language processing. Attention to detail and accuracy are crucial in this role.

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

To thrive as a Data Labeler, you need strong attention to detail, proficiency in data entry, and a basic understanding of computer operations, often supported by a high school diploma or equivalent. Experience with annotation platforms, labeling tools, or specific data management software is valuable and may be required for some roles. Effective time management, patience, and the ability to follow detailed instructions are standout soft skills in this position. These skills ensure the accurate and efficient preparation of high-quality datasets, which are crucial for training reliable machine learning models.

What does a typical day look like for a Data Labeler and how do team interactions work?

As a Data Labeler, your day typically involves reviewing, categorizing, and annotating large volumes of data such as images, text, or audio according to set guidelines. You’ll often work independently but may participate in regular team check-ins to discuss project updates, clarify instructions, or resolve ambiguous cases. Collaboration with data scientists or project managers is common when feedback or clarification is needed, ensuring consistency and quality across the labeled dataset. Over time, high-performing data labelers may transition into roles such as quality assurance reviewer or team lead. The work is detail-oriented and repetitive but is essential in powering reliable artificial intelligence and machine learning applications.

What is the role of a data labeler?

A data labeler is responsible for annotating and categorizing data, such as images, text, or videos, to help machine learning models understand and learn from the data. This role often involves using specialized tools and requires attention to detail to ensure accurate labeling, which is essential for training effective AI systems.
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Data Labeler jobs near you
Project Perseus \u007C Speech & Voice AI Analyst - Greek Speakers

Project Perseus \u007C Speech & Voice AI Analyst - Greek Speakers

Welo Data

Washington, DC

$26 - $28/hr

Full-time

Posted 4 days ago

Job description

Overview

Welo Data is looking for detail-oriented and reliable individuals to join our team as Data Labeling Analysts, supporting speech and voice AI systems.

This is a high-impact production role focused on building the datasets that power real-world AI systems. You’ll be working with audio, speech, and language data — helping ensure models are trained on accurate, well-structured, and representative inputs.

While this role is more execution-focused than evaluation-heavy roles, it still requires strong judgment, attention to detail, and consistency. The work sits at the intersection of language, data, and AI systems — where precision and discipline matter at scale.

We’re looking for people who are dependable, focused, and take pride in producing high-quality work, even across repetitive workflows.

Project Details
  • Job Title: Data Labeling Analyst
  • Hiring in: Onsite (Bay Area, Seattle, NYC, or client-dependent) 
  • Hours: Full-time, 40 hours per week
  • Employment Type: W2 Full-Time Employee
  • Work Authorization: Must be authorized to work in the U.S. (no visa sponsorship)
  • Pay Rate: $26 - $28/hour
Important: This is a 100% onsite position — remote work is not available for this role. To be considered, candidates must be located in or able to commute to one of the following cities: NYC, Seattle, Bellevue, Redmond, San Francisco, Sunnyvale, Burlingame, Austin, Los Angeles, Washington DC, Chicago, Boston. Please only apply if you meet this location requirement.
What You’ll Do
  • Execute high-volume data labeling and annotation tasks across speech and voice datasets
  • Follow detailed guidelines to ensure consistency, accuracy, and data integrity at scale
  • Work with audio and language data, including transcription, categorization, and tagging
  • Maintain strong throughput while meeting quality expectations
  • Escalate unclear or ambiguous cases appropriately
  • Adapt to evolving guidelines and workflows as systems and requirements change
  • Support baseline data production needs for AI training pipelines
  • Contribute to team calibrations and quality alignment sessions 
What We’re Looking For
  • Native-level fluency in Greek 
  • Strong written communication skills and language fundamentals
  • 1 year of work experience in data labeling, annotation, or content-focused work; or a Bachelor's degree or equivalent academic qualification in a related field.
  • Ability to follow detailed instructions and apply guidelines consistently
  • High attention to detail and ability to maintain accuracy in repetitive tasks
  • Comfort working in structured, process-driven environments
  • Ability to manage time effectively and maintain steady output
  • Willingness to ask questions and escalate when needed
  • Basic familiarity with AI, speech technology, or language data is a plus 
Benefits
  • Paid Vacation: 6 days
  • Paid Company Holidays: 2 days (Memorial Day and Labor Day)
  • Paid Sick Leave: accrued per applicable state law and company policy
  • Medical, Dental, and Vision Insurance (eligibility applies)
  • Health Savings Account (HSA)
  • 401(k) Retirement Plan
  • Employee Assistance Program
  • Additional voluntary benefits (life, accident, critical illness, etc.)
Onsite Perks (where applicable):
 Free breakfast, lunch, and dinner
Stocked micro-kitchens with snacks and beverages
Commuter benefits, including shuttles and bike-to-work options
Unique campus features depending on location
Why This Role

This role is a critical part of how modern AI systems are built. The data you produce directly impacts how speech and voice models understand and interact with real users.

It’s a great entry point into AI operations, offering exposure to large-scale systems and the opportunity to build foundational experience in data, language, and AI workflows.


Please note that in order to verify work authorization as is required by Federal law (I-9 process), all new employees must complete a live video verification with their selected IDs and provide photos of these selected IDs within their first 3 days of employment.
 
To know more details (Click here)
 
In compliance with federal law, all persons hired will be required to verify identity and eligibility to work in the United States and to complete the required employment eligibility verification form upon hire.  In addition, we employ anti-fraud checks to ensure all candidates meet the requirements of the program.
 
 
As a trusted global transformation partner, Welocalize accelerates the global business journey by enabling brands and companies to reach, engage, and grow international audiences. Welocalize delivers multilingual content transformation services in translation, localization, and adaptation for over 250 languages with a growing network of over 400,000 in-country linguistic resources. Driving innovation in language services, Welocalize delivers high-quality training data transformation solutions for NLP-enabled machine learning by blending technology and human intelligence to collect, annotate, and evaluate all content types. Our team works across locations in North America, Europe, and Asia serving our global clients in the markets that matter to them. www.welocalize.com
 
To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform essential functions.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.