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Data Labeling Jobs (NOW HIRING)

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

Data Labeling Specialist **Seeking entry level data specialists/IT for a robotics/AI company. Fresh graduates are encouraged to apply. Responsibilities * Use proprietary annotation tools to label ...

Data Labeling Specialist **Seeking entry level data specialists/IT for a robotics/AI company. Fresh graduates are encouraged to apply. Responsibilities * Use proprietary annotation tools to label ...

Data Labeling Specialist We are seeking a detail-oriented Data Labeling Specialist to join our innovative team. This position involves using proprietary annotation tools to label objects, poses, and ...

Data Labeling Specialist We are seeking a detail-oriented Data Labeling Specialist to join our innovative team. This position involves using proprietary annotation tools to label objects, poses, and ...

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Data Labeling information

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$10

$24

$57

How much do data labeling jobs pay per hour?

As of Jul 12, 2026, the average hourly pay for data labeling in the United States is $24.51, according to ZipRecruiter salary data. Most workers in this role earn between $16.11 and $28.12 per hour, depending on experience, location, and employer.

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.
More about Data Labeling jobs
What cities are hiring for Data Labeling jobs? Cities with the most Data Labeling job openings:
What are the most commonly searched types of Data Labeling jobs? The most popular types of Data Labeling jobs are:
What states have the most Data Labeling jobs? States with the most job openings for Data Labeling jobs include:
Infographic showing various Data Labeling job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, and 3% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $50,981 per year, or $24.5 per hour.
Data Labeling Associate

Data Labeling Associate

Welo Data

Bellevue, WA

$34/hr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 2 days ago


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


Working at Welo Data

What to expect from working at Welo Data

From Welo Data

About Welo Data, in their own words

From Welo Data

Welo Data is a global AI data services company powering the next generation of AI. We build, annotate, and validate the training datasets that make AI models accurate, safe, and ready for the real world — across languages, cultures, and domains.

Our team of experts spans the globe, combining deep technical knowledge with a human-centered approach. If you want your work to shape how AI understands the world, you'll find your place here.

Diversity and inclusion statement

From Welo Data

Our Strength is derived from Winning Together. Welo Data is unequivocally committed to developing and fostering a workplace and organizational culture that values the diversity of thought and perspective delivered by a diverse global workforce operating within an inclusive organization.