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Full Time Data Annotation Tech Jobs (NOW HIRING)

RWS Group

Data Annotator for AI Models (Italian)

$56 - $72.75/hr

... data annotation process. • Maintain high attention to detail and quality throughout the ... work full time, from 8:00 AM to 5:00 PM PST (Pacific Standard Time). • Bachelor's degree or ...

JPMorganChase

Data Domain Architect Lead

Wilmington, DE · On-site

... annotation and labeling methods • Experience with various data modeling techniques and tools • Familiar with Finance and Banking products • Broad expertise in data technologies; i.e., data ...

RWS Group

Data Annotator for AI Models (Dutch)

... alignment in the annotation process. Responsibilities : • Annotate data accurately and ... work full time, from 8:00 AM to 5:00 PM PST (Pacific Standard Time). • Bachelor's degree or ...

Sesame

Technical Program Manager, Data

San Francisco, CA · On-site

$152K - $196K/yr

They are seeking a Senior Technical Program Manager to lead their data collection and annotation ... Sesame is a voice tech startup focused on developing AI voice assistants that create natural and ...

J.P. Morgan

Data Domain Architect Lead

Columbus, OH

Familiar with industry annotation and labeling methods * Experience with various data modeling techniques and tools * Familiar with Finance and Banking products * Broad expertise in data technologies ...

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Full Time Data Annotation Tech information

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$12

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$34

How much do full time data annotation tech jobs pay per hour?

As of Jul 15, 2026, the average hourly pay for full time data annotation tech in the United States is $22.84, according to ZipRecruiter salary data. Most workers in this role earn between $16.83 and $27.16 per hour, depending on experience, location, and employer.

How much does a data annotation tech make per hour?

A full-time data annotation technician typically earns between $12 and $20 per hour, depending on experience, location, and the complexity of annotation tasks. Many roles require attention to detail and familiarity with annotation tools or platforms.

Can you do data annotation full time?

Full-time data annotation roles are available and typically involve working set hours, often 40 hours per week. These positions may require familiarity with annotation tools and attention to detail, and they often offer consistent schedules and remote or on-site options.

How hard is it to get hired by data annotation?

Getting hired as a full-time data annotation technician typically requires basic computer skills, attention to detail, and sometimes familiarity with annotation tools or platforms. The hiring process is generally straightforward, with many companies offering entry-level positions that do not require extensive experience or certifications.

How does a Full Time Data Annotation Tech typically collaborate with data scientists and engineers on projects?

As a Full Time Data Annotation Tech, you will regularly work alongside data scientists and engineers to ensure the accuracy and quality of labeled datasets used for machine learning models. Collaboration often involves attending project meetings to clarify annotation guidelines, providing feedback on ambiguous data cases, and updating annotation processes based on team input. Clear communication is essential, as your work directly impacts model performance and downstream analytics. This team-oriented environment fosters learning and provides insight into broader AI development workflows.

What are Full Time Data Annotation Techs?

Full Time Data Annotation Techs are professionals responsible for labeling and categorizing data used to train machine learning models. They examine various types of data, such as images, text, or audio, and apply specific tags or annotations according to project guidelines. Their work is essential in ensuring the accuracy of artificial intelligence systems by providing high-quality, structured datasets. Full-time positions typically involve working standard business hours and may require familiarity with specialized annotation tools and attention to detail.

What are the key skills and qualifications needed to thrive as a Full Time Data Annotation Tech, and why are they important?

To thrive as a Full Time Data Annotation Tech, you need strong attention to detail, basic data management skills, and familiarity with data labeling practices, typically supported by a high school diploma or equivalent. Experience with annotation tools (such as Labelbox, Supervisely, or similar platforms) and basic proficiency in spreadsheet or database systems are commonly required. Reliability, consistency, and effective communication are crucial soft skills for quality assurance and collaboration with data teams. These skills and qualities are essential to ensure the accuracy and efficiency of annotated datasets, which directly impact the performance of machine learning models.

What is the difference between Full Time Data Annotation Tech vs Data Labeling Specialist?

AspectFull Time Data Annotation TechData Labeling Specialist
CredentialsBasic computer skills, attention to detailSimilar credentials, often with training in labeling tools
Work EnvironmentOffice or remote, collaborative teamsRemote or on-site, focused on labeling tasks
Industry UsageAI, machine learning, tech companiesAI, autonomous vehicles, healthcare
Job FocusAnnotating data for machine learning modelsLabeling data to improve AI accuracy

Both roles involve data annotation and labeling, often requiring similar skills and working environments. The main difference lies in job titles used by employers and the scope of responsibilities, with 'Full Time Data Annotation Tech' emphasizing a broader technical role, while 'Data Labeling Specialist' may focus more on specific labeling tasks.

Can you make a living off data annotation?

Full Time Data Annotation Tech roles can provide a stable income, especially with consistent work and experience. However, pay rates vary depending on the employer, location, and complexity of tasks, and many positions are part-time or freelance, which may affect earning potential.
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What states have the most Full Time Data Annotation Tech jobs? States with the most job openings for Full Time Data Annotation Tech jobs include:
What job categories do people searching Full Time Data Annotation Tech jobs look for? The top searched job categories for Full Time Data Annotation Tech jobs are:
Full Time Data Annotation Tech jobs near you
Infographic showing various Full Time Data Annotation Tech job openings in the United States as of July 2026, with employment types broken down into 2% Locum Tenens, 19% Full Time, 17% Part Time, 19% Contract, 42% Nights, and 1% Summer. Highlights an 34% Physical, and 66% Remote job distribution, with an average salary of $47,512 per year, or $22.8 per hour.
Data Annotation Specialist - Seattle (On Site)

Data Annotation Specialist - Seattle (On Site)

Welo Data

Seattle, WA

Full-time

Re-posted 2 days ago

Job description

OVERVIEW

Welo Data is looking for a skilled Data Analyst to join our team and contribute to advancing AI technologies. This role offers a unique opportunity to engage directly with cutting-edge AI products, supporting the refinement and performance of machine learning models through precise data analysis and quality assurance.

Project Details
Job Title: Data Analyst
Location: Seattle (On-site)
Hours: Full-time, 40 hours per week
Start Date: November 2025
Employment Type: W2 Full-Time Employee

Must have valid work authorization in the US (Welocalize does not sponsor VISAs at this time).

This role is an incredible chance to be at the forefront of AI technology, helping shape the future by testing new products, updating machine learning models, and ensuring high-quality data for impactful AI solutions.
Key Responsibilities
  • Test new AI products and provide actionable feedback to improve functionality and user experience.
  • Conduct detailed data annotation and quality assurance of natural language datasets following established guidelines.
  • Collaborate in updating and refining machine learning models to boost accuracy and effectiveness.
  • Analyze data for consistency, relevancy, and alignment with project goals.
  • Perform quality control to identify and report anomalies, error patterns, and discrepancies.
  • Use basic data analysis methods to extract insights and support continuous improvement.
  • Prepare clear and concise reports on findings, including observations on data quality, AI model performance, and user feedback.
Preferred Qualifications
  • University degree in linguistics, translation, or a related field.
  • 3-5 years of professional linguistics experience.
  • Strong analytical skills with the ability to detect patterns and anomalies.
  • Excellent communication skills and the ability to work collaboratively in a fast-paced environment.
  • Adaptability to evolving priorities and project requirements.
Benefits
  • Paid Sick Time & Paid Holiday (combined): 15 days
  • Paid Holidays: Memorial Day and Labor Day
  • Medical Insurance (subject to eligibility requirements)
  • Dental Insurance
  • Vision Insurance
  • Health Savings Account (HSA)
  • Voluntary Life Insurance
  • Accident, Critical Illness, and Hospital Indemnity Insurance
  • Telemedicine Benefit
  • 401(k) Retirement Plan
  • Employee Assistance Program
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 and identifying potential inconsistencies or verification signals in application materials based on available information. 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.

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.