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Seasonal 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 ... Build a data annotation team * Own annotation operations end-to-end * Manage the people side of ...

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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Seasonal Data Annotation Tech information

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

As of Aug 6, 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 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.

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.

Is data annotation tech still hiring?

Data annotation technician roles are currently in demand as companies continue to develop AI and machine learning models. These positions often require attention to detail and familiarity with annotation tools, and they may be available on flexible or remote schedules. Job availability can vary by industry and region, but overall, hiring for data annotation roles remains active.

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.

Can I do data annotation with no experience?

Seasonal Data Annotation Tech roles typically do not require prior experience, as training is often provided to teach the necessary skills. Basic computer literacy and attention to detail are usually sufficient to start, and familiarity with annotation tools can be learned on the job. These positions are suitable for beginners looking to enter data labeling work without extensive background.
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What cities are hiring for Seasonal Data Annotation Tech jobs? Cities with the most Seasonal Data Annotation Tech job openings:
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What job categories do people searching Seasonal Data Annotation Tech jobs look for? The top searched job categories for Seasonal Data Annotation Tech jobs are:
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, 83% Full Time, 12% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $47,512 per year, or $22.8 per hour.

Data Annotation Lead

Sunday Inc

Redwood City, CA • On-site

Full-time

Re-posted yesterday

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 operation side of data annotation and scale the team behind it.
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
  • Own annotation operations end-to-end
  • 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
  • Own the in-house vs. vendor mix and manage external partners where used

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
  • Previously a top 2% annotator yourself in the past
  • 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