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Freelance Ai Data Labeling Jobs (NOW HIRING)

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 ...

Seeking entry level data specialists/IT for a robotics/AI company. Fresh graduates are encouraged to apply. Responsibilities * Use proprietary annotation tools to label objects, poses, and ...

Data Labeling Specialist We are seeking a detail-oriented Data Labeling Specialist to join our ... Join a first-of-its-kind AI robotics company focused on bringing a general-purpose humanoid to life.

AI Engagement Manager

$150K - $180K/yr

Partner with Product, Delivery, and Engineering to design solutions for Agentic AI, data labeling, evaluation, RLHF, red-teaming, and emerging workflows * Ensure strong requirements gathering ...

Seeking entry level data specialists/IT for a robotics/AI company. Fresh graduates are encouraged to apply. Responsibilities * Use proprietary annotation tools to label objects, poses, and ...

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Freelance Ai Data Labeling information

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$14

$47

$132

How much do freelance ai data labeling jobs pay per hour?

As of Jul 18, 2026, the average hourly pay for freelance ai data labeling in the United States is $47.71, according to ZipRecruiter salary data. Most workers in this role earn between $24.28 and $61.78 per hour, depending on experience, location, and employer.

What is freelance AI data labeling?

Freelance AI data labeling involves working independently to annotate or tag data, such as images, text, audio, or video, to help train artificial intelligence and machine learning models. Freelancers are hired by companies or platforms to manually identify and categorize data so that algorithms can learn to recognize patterns and make accurate predictions. This work is essential for improving the accuracy and performance of AI systems in various applications, including self-driving cars, voice assistants, and content moderation. Typically, freelancers need attention to detail, basic technical skills, and sometimes domain-specific knowledge, depending on the project's requirements.

What is the difference between Freelance Ai Data Labeling vs Data Annotation Specialist?

AspectFreelance Ai Data LabelingData Annotation Specialist
CredentialsNone required, but familiarity with labeling tools helpsOften requires training or certification in annotation tools
Work EnvironmentRemote, flexible freelance projectsTypically employed by companies or agencies, sometimes remote
Employer & IndustryFreelance platforms, AI/ML industryTech companies, AI development teams
Search & Comparison IntentLooking for freelance labeling jobsSeeking full-time or contract annotation roles

Freelance Ai Data Labeling involves independently completing labeling tasks for various clients, offering flexibility and project-based work. Data Annotation Specialists often work within organizations or agencies, focusing on detailed annotation tasks as part of a team. Both roles require knowledge of labeling tools, but freelancers typically have more varied projects, while specialists may have more structured employment settings.

What are the key skills and qualifications needed to thrive as a Freelance AI Data Labeler, and why are they important?

To thrive as a Freelance AI Data Labeler, you need strong attention to detail, basic understanding of machine learning concepts, and the ability to follow complex guidelines accurately, usually supported by a high school diploma or higher education. Familiarity with data annotation platforms, labeling tools (like Labelbox or Supervisely), and sometimes specific domain knowledge is often required. Excellent time management, reliability, and clear communication help freelancers stand out in delivering high-quality, consistent results. These skills ensure that labeled data is accurate and reliable, directly impacting the effectiveness of AI models and client satisfaction.

What are some typical challenges faced by freelance AI data labelers, and how can they be managed?

Freelance AI data labelers often encounter challenges such as maintaining accuracy while working with large volumes of repetitive data, understanding complex labeling guidelines, and managing tight deadlines across multiple clients. Effective strategies include regularly reviewing project instructions, using productivity tools to track progress, and seeking clarification from clients when uncertainties arise. Maintaining open communication with project managers and participating in feedback sessions can also help improve labeling quality and efficiency.
More about Freelance Ai Data Labeling jobs
What cities are hiring for Freelance Ai Data Labeling jobs? Cities with the most Freelance Ai Data Labeling job openings:
What are the most commonly searched types of Ai Data Labeling jobs? The most popular types of Ai Data Labeling jobs are:
What states have the most Freelance Ai Data Labeling jobs? States with the most job openings for Freelance Ai Data Labeling jobs include:
What job categories do people searching Freelance Ai Data Labeling jobs look for? The top searched job categories for Freelance Ai Data Labeling jobs are:
Infographic showing various Freelance Ai Data Labeling job openings in the United States as of July 2026, with employment types broken down into 75% Full Time, 22% Part Time, and 3% Contract. Highlights an 66% Physical, 3% Hybrid, and 31% Remote job distribution, with an average salary of $99,230 per year, or $47.7 per hour.
Data Labeling Associate

Data Labeling Associate

Welo Data

Seattle, WA

$34/hr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 8 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.