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Full Time Data Annotation Tech Jobs (NOW HIRING)

Sunday Inc

Data Annotation Lead

Redwood City, CA · On-site

... our technology. We are now seeking passionate individuals to join us in the next phase of our ... This role is about building and leading a world class in-house data annotation team that is able to ...

Encord

Human Data Operations Strategist

San Francisco, CA · On-site

$130K - $210K/yr

Oversee data annotation projects, translating complex AI and machine learning requirements into ... or technology companies * Proven ability to own complex, multi-stakeholder workflows end-to-end ...

Encord

Human Data Operations Strategist

San Francisco, CA · On-site

$130K - $210K/yr

Oversee data annotation projects, translating complex AI and machine learning requirements into ... technology companies * Proven ability to own complex, multi-stakeholder workflows end-to-end ...

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Full Time Data Annotation Tech information

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$12

$22

$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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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 Lead

Data Annotation Lead

Sunday Inc

Redwood City, CA • On-site

Full-time

Re-posted 9 days ago

Job description

Join Us in Building the Future of Home Robotics
At Sunday, we're developing personal robots to reclaim the hours lost to repetitive tasks. We're focused on an ambitious goal to make generalized robots broadly accessible, enabling households to take back quality time.
We have spent the last 18 months building a talented team, securing capital, and validating our technology. We are now seeking passionate individuals to join us in the next phase of our growth. If you are ready to apply your skills to the forefront of robotics innovation, we'd love to hear from you.
What to Expect
We're looking for a Data Annotations Lead to join our Data team and own the people side of data annotation.
This role is about building and leading a world class in-house data annotation team that is able to pivot quickly to any research experiment while delivering on quality, quantity, and variety when it comes to data.
You'll work in coordination with Machine Learning, Software engineering, and Data to define the framework and tools on which to build a data annotation team around. Your role is vital to ensuring our data annotators are aligned with the guidances for annotations and are upholding a culture of happiness.
What You'll Do
  • Build a data annotation team
  • Manage the people side of data annotations
  • Create documentation
  • Be in the weeds and annotate data yourself anytime something new is being designed
  • Create data annotation processes
  • Vibe code data annotation tools during pilot stages

What You'll Bring
  • Clear written and verbal communication to guide our data annotators
  • Your ability to manage unexpected challenges
  • Your ownership of key stakeholders with data annotators, engineering, and support
  • Excitement for the growth and development of data annotation
  • Someone adept at prioritization of competing requests, who's able to move both quickly, and in an organized manner
  • A level of hardcore-ness while still treating people like people
  • Intermediate level understanding of ML

Nice to Have
  • Previous experience leading data annotation teams
  • Technical skills to build tools for data annotation
  • Ability to leverage AI to help improve productivity

At Sunday Robotics, we're building technology shaped by real people - curious, creative, and diverse. We're proud to be an equal opportunity employer and consider all qualified applicants regardless of race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.
Even if you don't meet every single requirement, we encourage you to apply. Studies show that women and underrepresented groups often hold back unless they meet 100% of the criteria - we don't want that to be the reason we miss out on great talent.

Apply