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Seasonal Data Annotation Tech Jobs (NOW HIRING)

TEKsystems

Data Annotation Specialist

Seattle, WA · Remote

$20/hr

Use annotation tools to mark up text, images, or other data according to specific guidelines ... As an industry leader in Full-Stack Technology Services, Talent Services, and real-world ...

Q Analysts

Data Annotation Technician

Kirkland, WA · On-site

Data Annotation Technician Join Q Analysts and become part of a world-class organization. Q ... Q Analysts is a high growth technology consulting company with a focus on providing Quality ...

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How much do seasonal data annotation tech jobs pay per hour?

As of Aug 26, 2026, the average hourly pay for seasonal 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.

What is a seasonal data annotation tech?

A Seasonal Data Annotation Tech is a temporary employee who labels, tags, or categorizes data—such as images, audio, or text—to help train artificial intelligence and machine learning models. Their work ensures that algorithms can recognize patterns and make predictions accurately. These roles are typically available during peak business periods or large-scale data projects and often involve repetitive but detail-oriented tasks. Seasonal Data Annotation Techs usually work under supervision and may use specialized annotation tools or software. This job is important for improving the quality and reliability of AI systems.

What are the key skills and qualifications needed to thrive as a seasonal data annotation tech?

To thrive as a Seasonal Data Annotation Tech, you need strong attention to detail, basic computer literacy, and familiarity with data labeling concepts, often supported by a high school diploma or equivalent. Experience with annotation platforms, spreadsheet software, and sometimes proprietary labeling tools is typically required. Reliability, time management, and the ability to follow precise instructions are standout soft skills in this role. These skills ensure accurate, high-quality data labeling, which is critical for training machine learning models and supporting AI development.

What are the main challenges seasonal data annotation techs face during peak project periods?

Seasonal Data Annotation Techs often experience high workloads during peak project periods, which can involve processing large volumes of data under tight deadlines. Maintaining accuracy and consistency while labeling or categorizing data is crucial, as even small errors can impact the quality of machine learning models. Techs must also adapt quickly to changes in project guidelines and collaborate with team members to resolve ambiguities. Staying focused and managing repetitive tasks efficiently are key to success in this fast-paced environment.

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

AspectSeasonal Data Annotation TechData Labeling Specialist
CredentialsHigh school diploma or equivalent; training in annotation toolsHigh school diploma or equivalent; training in labeling software
Work EnvironmentTech companies, AI development teams, remote or on-siteTech firms, AI companies, remote or on-site
Industry UsageUsed during peak seasons for AI model trainingUsed for ongoing data labeling projects

Seasonal Data Annotation Tech typically works during specific peak periods to prepare data for AI models, often focusing on large batches. Data Labeling Specialists perform continuous data annotation tasks, often with more detailed labeling requirements. Both roles require familiarity with annotation tools but differ mainly in timing and project scope.

Is data annotation tech still hiring?

Data annotation technician roles are currently in demand as companies expand AI and machine learning projects. These positions often require attention to detail and familiarity with annotation tools, and they are frequently available on flexible or remote schedules. Job availability can vary by industry and region, but overall, hiring for data annotation roles remains active.
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Seasonal Data Annotation Tech jobs near you
Infographic showing various Seasonal Data Annotation Tech job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution, with an average salary of $47,512 per year, or $22.8 per hour.

Data Annotation Specialist

Austin, TX • On-site

Saronic Technologies
Guided Missile and Space Vehicle Manufacturing • 51 - 200 employees
Learn more about Saronic Technologiesexternal

Contractor

Re-posted 7 days ago

Job description

Saronic Technologies is a leader in revolutionizing autonomy at sea, dedicated to developing state-of-the-art solutions that enhance maritime operations through autonomous and intelligent platforms.
Job Overview
We are seeking a Data Annotation Specialist to annotate and review visual datasets used to train and evaluate machine-learning models for maritime perception and autonomy. This role supports our software, perception, and autonomy teams by ensuring labeled data is accurate, consistent, and useful for model development.
The ideal candidate has prior computer vision annotation experience, strong visual attention to detail, and the ability to maintain speed and accuracy through repetitive labeling work. This person should be comfortable following detailed instructions, adapting as labeling rules change, and supporting a fast-moving technical team.
This is an on-site, full-time contract role with an intended path to full-time conversion based on performance and business needs. Upon conversion, the employee would be eligible for Saronic's standard full-time benefits. This position reports to the Data Annotation Manager.
Responsibilities
  • Annotate and review large volumes of image, video, infrared, and other sensor data using computer vision labeling methods.
  • Identify vessels, objects, environmental features, and other elements relevant to maritime autonomy.
  • Maintain accuracy, consistency, and productivity across repetitive, detail-heavy datasets.
  • Apply evolving labeling guidelines and escalate unclear edge cases when needed.
  • Perform both manual annotation work and quality review of auto-labeled data as needed.
  • Willingness to support priority project deadlines when needed.
Qualifications
  • Prior experience in computer vision data annotation or labeling.
  • Familiarity with annotation tools such as Labelbox, CVAT, or similar
  • Experience with annotation types such as segmentation masks, bounding boxes, key points, object tracking, or classification.
  • Strong visual pattern recognition, spatial reasoning, and attention to detail.
  • Comfortable performing repetitive, process-driven work for extended periods while maintaining quality.
  • Able to adapt to changing project priorities, labeling rules, and quality standards in a fast-paced environment.
  • Strong communication skills and willingness to ask questions, accept feedback, and collaborate with the team.
  • Basic understanding of maritime environments, autonomous systems, robotics, or defense technology is a plus.

Saronic CCPA Notice for Candidates and California Employees
If this role is based in the United States, it requires access to export-controlled information or items that require "U.S. Person" status. As defined by U.S. law, individuals who are any one of the following are considered to be a "U.S. Person": (1) U.S. citizens, (2) legal permanent residents (a.k.a. green card holders), and (3) certain protected classes of asylees and refugees, as defined in 8 U.S.C. 1324b(a)(3).
Saronic does not discriminate on the basis of race, sex, color, religion, age, national origin, marital status, disability, veteran status, genetic information, sexual orientation, gender identity or any other reason prohibited by law in provision of employment opportunities and benefits. We are also committed to providing reasonable accommodations for qualified individuals with disabilities.

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