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Data Labelling Jobs in Washington, DC (NOW HIRING)

Welocalize

Data Labeling Associate

Washington, DC

$34/hr

WHAT YOU'LL DO • Execute Data labelling and annotation tasks across speech and voice datasets. • Work with audio and language data, including transcription, categorization, and tagging. YOU ARE A ...

Welocalize

Data Labeling Associate

Washington, DC

$34/hr

WHAT YOU'LL DO • Execute Data labelling and annotation tasks across speech and voice datasets. • Work with audio and language data, including transcription, categorization, and tagging. YOU ARE A ...

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Data Labelling information

See Washington, DC salary details

$52.1K

$186.9K

$275.8K

How much do data labelling jobs pay per year?

As of Jul 4, 2026, the average yearly pay for data labelling in Washington, DC is $186,899.00, according to ZipRecruiter salary data. Most workers in this role earn between $151,200.00 and $192,500.00 per year, depending on experience, location, and employer.

What does a data labeler do?

A data labeler is responsible for annotating and categorizing data such as images, videos, or text to help train machine learning models. They use tools and guidelines to ensure accurate labeling, which is essential for developing reliable AI systems. Attention to detail and understanding of the data are important for this role.

Is data labelling a good career?

Data labelling is a common entry-level role in data annotation and machine learning workflows, often requiring attention to detail and familiarity with labeling tools. It can offer flexible schedules and opportunities to develop skills in AI and data management, but typically involves repetitive tasks and lower pay compared to more advanced tech roles.

What is a Data Labelling job?

A Data Labelling job involves annotating data, such as text, images, audio, or video, to help train machine learning models. Labelers categorize or tag data by following specific guidelines to ensure accuracy and consistency. This process is essential for improving AI applications, including image recognition, natural language processing, and autonomous systems. Attention to detail and adherence to instructions are key skills required for this role.

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 for AI training. It is often performed remotely and may involve repetitive tasks with a focus on accuracy.

What are the typical daily responsibilities of a Data Labelling professional?

Data Labelling professionals are generally responsible for reviewing and accurately annotating large volumes of data—such as images, audio, video, or text—to support machine learning and AI projects. This often involves using specialized labeling platforms and following detailed guidelines provided by data scientists or project managers. You may also participate in regular team meetings to discuss quality standards or address ambiguities in data, and your work is typically reviewed for accuracy before being integrated into training datasets. Collaborating with other data annotators, engineers, and analysts is a common part of the process to ensure consistency and high-quality results.

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

To thrive as a Data Labelling professional, you need strong attention to detail, proficiency with data annotation processes, and a basic understanding of machine learning concepts. Familiarity with annotation tools like Labelbox, Supervisely, or Amazon SageMaker Ground Truth is often required, and some roles may value certifications in data processing or AI fundamentals. Reliability, patience, and the ability to follow precise instructions are important soft skills for success in this position. These skills ensure accurate and consistent data labeling, which is critical for developing effective AI models and maintaining data integrity.

How can I get started in data labeling?

To start in data labeling, gain familiarity with annotation tools like Labelbox or CVAT and understand data privacy requirements. Basic skills in image, text, or audio annotation are helpful, and some roles may require attention to detail and the ability to follow guidelines. Entry-level positions often provide training, making it accessible for beginners.
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Data Labelling jobs near you
Data Labeling Associate

Data Labeling Associate

Welocalize

Washington, DC

$34/hr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 25 days ago

Welocalize rating

5.9

Company rating: 5.9 out of 10

Based on 10 frontline employees who took The Breakroom Quiz

345th of 437 rated business services

Job description

What if your language expertise could help improve the speech and voice AI systems used by millions of people worldwide?
WHAT YOU’LL DO
• Execute Data labelling and annotation tasks across speech and voice datasets.
• Work with audio and language data, including transcription, categorization, and tagging.
YOU ARE A FIT IF YOU’RE…
• A English with Dialect from (Australian, United Kingdom and Canadian) speaker with strong written communication skills
• Experienced in data labelling, annotation, content review, or similar detail-oriented work (2+ year preferred)
• A Bachelor's degree holder
PROJECT DETAILS
• Location: 100% Onsite (Bay Area, Seattle, NYC, or client-dependent locations)
• Employment Type: W2 Full-Time Employee
• Hours: 40 hours per week
• Work Authorization: Must be authorized to work in the U.S. (no visa sponsorship available)
• Eligible Locations: NYC, Seattle, Bellevue, Redmond, San Francisco, Sunnyvale, Burlingame, Austin, Los Angeles, Washington DC, Chicago, and Boston
BENEFITS
• $34 per hour
• Paid Vacation (6 days)
• Paid Company Holidays
• Paid Sick Leave
• Employee Assistance Program
• Health Savings Account (HSA)
• 401(k) Retirement Plan
• Additional Voluntary Benefits (Life, Accident, Critical Illness, etc.)
ADDITIONAL BENEFITS (Upon Eligibility)
• Medical, Dental, and Vision Insurance
• Free Breakfast, Lunch, and Dinner (where applicable)
• Stocked Micro-Kitchens with Snacks and Beverages
• Commuter Benefits, Including Shuttles and Bike-to-Work Options
• Unique Campus Amenities Depending on Location

Company Description

Welocalize enables brands to reach and grow global audiences through services and solutions for translation, localization, adaptation, and automation. We offer multilingual solutions to transform all content types for local audiences, at every step of our clients’ global business journey. We have 1,500 global team members across offices in North America, Europe and Asia dedicated to helping some of the world’s largest brands operate and succeed internationally.

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