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Seasonal Data Annotation Tech Jobs (NOW HIRING)

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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Seasonal Data Annotation Tech information

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

As of Jul 16, 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.

Does data annotation tech really pay?

Data annotation technicians typically earn hourly wages that range from minimum wage to around $15-$20 per hour, depending on experience and the employer. Some positions offer bonuses or flexible schedules, but overall pay is generally modest compared to other tech roles. Compensation can vary based on the complexity of annotation tasks and the company's location.

How to get jobs on data annotation tech?

To get a job as a seasonal data annotation technician, build skills in data labeling, familiarize yourself with annotation tools like Labelbox or CVAT, and create a strong resume highlighting attention to detail and technical aptitude. Many companies hire through online job boards or directly on their websites, and having prior experience or certifications in data management can improve your chances.

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, and why are they important?

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 real or fake?

Data annotation is a real and essential process in machine learning and AI development, involving labeling data such as images, text, or audio to train algorithms. Data annotation jobs, including those for seasonal data annotation tech roles, require attention to detail and familiarity with annotation tools. The work is legitimate and widely used in the tech industry.

How hard is it to get a job with data annotation tech?

Securing a position as a seasonal data annotation technician typically requires basic computer skills, attention to detail, and sometimes familiarity with annotation tools. Many roles are entry-level and do not require advanced certifications, making them accessible to a wide range of applicants, though competition can vary based on demand and location.

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.
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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 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 Quality Control Analyst- St. Louis

Data Annotation Quality Control Analyst- St. Louis

Enabled Intelligence

Saint Louis, MO • On-site

Full-time

Posted 20 days ago

Job description

Data Annotation

Quality Control Analyst

About Enabled Intelligence, Inc.

Enabled Intelligence, Inc. provides extremely accurate, precise and secure data labeling and AI solutions to help our government and commercial customers effectively deploy reliable and unbiased artificial intelligence technologies. We leverage the unique talents of veterans, people with different abilities, and subject matter experts to unlock the value of data to improve the delivery of public services and mission critical national security programs. Every Enabled solution starts with a team of highly-trained, US based data analysts that have both subject-matter expertise as well as a deep understanding of the best techniques and tools for AI data annotation, model development, and testing and evaluation.

At EI we respect and celebrate individuals from all walks of life. Our different backgrounds, cultures, experiences, and way of thinking make us stronger together and result in the most accurate and reliable AI solutions for our clients. We are extremely committed to a culture and environment where excellence can be achieved! If the idea of working in a collaborative, energetic and people focused environment where we are working together to build something meaningful excites you, Enabled Intelligence might just be the team you are looking for!

Data Annotation Quality Control Analyst

Data annotation is an essential component in training artificial intelligence/machine learning (AI/ML) algorithms. Accuracy of the data used to train AI models is one of the biggest factors in the effectiveness of the AI performance. As a member of the Enabled Intelligence Quality Control team, your role is to help ensure our clients receive the highest quality of data. You will review data such as geospatial imagery (EO, RGB, IR, SAR), Full Motion Video, and types of documents that have been annotated to identify and correct errors such as missed objects, miss-classifications and false positives. You will be responsible for recognizing patterns and sharing this analysis with project managers and the director of Quality Delivery. Joining our team means playing an integral role for the future of government AI/ML capabilities.

Responsibilities

  • Use advanced analytic tools to review data (EO, RGB, IR, SAR, FMV) that has been annotated to identify and correct errors such as missed objects, miss-classifications and false positives
  • Diligently track and analyze patterns of errors and keep Project Managers and the Director of Quality Delivery up to date
  • Process project data according to established procedures and guidelines
  • Provide feedback and ideas on process improvements or concerns that may impact project performance

Required Qualifications and Skills

  • Strong computer skills including proficiency in Excel and PowerPoint
  • Strong analytical skills, visual spatial recognition, pattern recognition and attention to detail
  • Ability to follow directions and meet deadlines
  • Ability to communicate reliably
  • Ability to be a team player and work with individuals with different communication, learning and working styles
  • Ability to work independently including managing your schedule, attending all required meetings and completing projects within a deadline
  • Ability to work out of the Enabled Intelligence office located in St. Louis, MO Monday-Friday during normal business hours
  • Must be a US Citizen

Desired Qualifications and Skills

  • Previous imagery-based Data Annotation or feature extraction experience including EO, RGB, IR, SAR and/or FMV
  • Previous Data Annotation Quality Control experience
  • Ability to answer project questions and provide one on one performance feedback to Data Annotators
  • Prior experience with business productivity tools like Microsoft Office, and/or Slack
  • Highschool Degree

Physical Requirements

Prolonged periods of sitting at a desk and working on a computer

Background Check & Security Clearance

Applicants selected will be subject to background investigation and must meet requirements for employment.


Apply