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Seasonal Data Annotation Tech Jobs (NOW HIRING)

Amazon

Catalog Specialist, RCX

Bellevue, WA · On-site

Key job responsibilities • Work closely with our product, technology, and science teams to support Machine Learning (ML) models • Perform data annotation required to train and evaluate ML models ...

Amazon

Catalog Specialist, RCX

Bellevue, WA · On-site

Key job responsibilities • Work closely with our product, technology, and science teams to support Machine Learning (ML) models • Perform data annotation required to train and evaluate ML models ...

TSMG

AI/ML Data Contributor

Louisville, KY · Remote

Previous experience in data annotation, QA, or testing * Interest in AI, machine learning, or emerging technologies What We Offer * Paid, flexible task-based work * Opportunity to work on innovative ...

TSMG

AI/ML Data Contributor

Los Angeles, CA · Remote

Previous experience in data annotation, QA, or testing * Interest in AI, machine learning, or emerging technologies What We Offer * Paid, flexible task-based work * Opportunity to work on innovative ...

TSMG

AI/ML Data Contributor

Boise, ID · Remote

Previous experience in data annotation, QA, or testing * Interest in AI, machine learning, or emerging technologies What We Offer * Paid, flexible task-based work * Opportunity to work on innovative ...

TSMG

AI/ML Data Contributor

Birmingham, AL

Previous experience in data annotation, QA, or testing * Interest in AI, machine learning, or emerging technologies What We Offer * Paid, flexible task-based work * Opportunity to work on innovative ...

TSMG

AI/ML Data Contributor

Birmingham, AL

Previous experience in data annotation, QA, or testing * Interest in AI, machine learning, or emerging technologies What We Offer * Paid, flexible task-based work * Opportunity to work on innovative ...

TSMG

AI/ML Data Contributor

Louisville, KY · On-site

Previous experience in data annotation, QA, or testing * Interest in AI, machine learning, or emerging technologies What We Offer * Paid, flexible task-based work * Opportunity to work on innovative ...

TSMG

AI/ML Data Contributor

Columbia, SC

Previous experience in data annotation, QA, or testing * Interest in AI, machine learning, or emerging technologies What We Offer * Paid, flexible task-based work * Opportunity to work on innovative ...

TSMG

AI/ML Data Contributor

Des Moines, IA

Previous experience in data annotation, QA, or testing * Interest in AI, machine learning, or emerging technologies What We Offer * Paid, flexible task-based work * Opportunity to work on innovative ...

TSMG

AI/ML Data Contributor

Jackson, MS

Previous experience in data annotation, QA, or testing * Interest in AI, machine learning, or emerging technologies What We Offer * Paid, flexible task-based work * Opportunity to work on innovative ...

TSMG

AI/ML Data Contributor

Chicago, IL · Remote

Previous experience in data annotation, QA, or testing * Interest in AI, machine learning, or emerging technologies What We Offer * Paid, flexible task-based work * Opportunity to work on innovative ...

TSMG

AI/ML Data Contributor

Columbia, SC · On-site

Previous experience in data annotation, QA, or testing * Interest in AI, machine learning, or emerging technologies What We Offer * Paid, flexible task-based work * Opportunity to work on innovative ...

TSMG

AI/ML Data Contributor

Philadelphia, PA · On-site

Previous experience in data annotation, QA, or testing * Interest in AI, machine learning, or emerging technologies What We Offer * Paid, flexible task-based work * Opportunity to work on innovative ...

TSMG

AI/ML Data Contributor

Boise, ID · Remote

Previous experience in data annotation, QA, or testing * Interest in AI, machine learning, or emerging technologies What We Offer * Paid, flexible task-based work * Opportunity to work on innovative ...

TSMG

AI/ML Data Contributor

Wichita, KS

Previous experience in data annotation, QA, or testing * Interest in AI, machine learning, or emerging technologies What We Offer * Paid, flexible task-based work * Opportunity to work on innovative ...

TSMG

AI/ML Data Contributor

Fargo, ND · Remote

Previous experience in data annotation, QA, or testing * Interest in AI, machine learning, or emerging technologies What We Offer * Paid, flexible task-based work * Opportunity to work on innovative ...

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All JobsSeasonal Data Annotation Tech Jobs

Seasonal Data Annotation Tech information

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$12

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$34

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

As of Jun 25, 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 the employer and location. The pay can increase with experience, skill in specific tools, or certification, and some roles offer flexible or remote schedules. Overall, it provides a steady income but is generally considered an entry-level or part-time position.

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 it hard to get a job at 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. While the entry process can be straightforward, competition varies depending on the company and location, and some roles may require minimal prior experience or training.

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 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, familiarity with annotation tools, and the ability to work remotely or on flexible schedules. Hiring trends can vary by industry and region, but overall demand remains steady for skilled annotation workers.

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 use ChatGPT for data annotation?

As a Seasonal Data Annotation Tech, using ChatGPT for data annotation is possible but limited. ChatGPT can assist in generating or reviewing text labels, but it may require human oversight to ensure accuracy and consistency in annotated data. Typically, specialized annotation tools and guidelines are preferred for high-quality data labeling tasks.
More about Seasonal Data Annotation Tech jobs
What cities are hiring for Seasonal Data Annotation Tech jobs? Cities with the most Seasonal Data Annotation Tech job openings:
What are the most commonly searched types of Data Annotation Tech jobs? The most popular types of Data Annotation Tech jobs are:
What states have the most Seasonal Data Annotation Tech jobs? States with the most job openings for Seasonal Data Annotation Tech jobs include:
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 June 2026, with employment types broken down into 1% As Needed, 75% Full Time, 21% Part Time, and 3% 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 Domain Architect Lead

Data Domain Architect Lead

JPMorgan Chase & Co.

Wilmington, DE • On-site

Full-time

Medical, Retirement

Posted 21 days ago

JPMorgan Chase & Co. rating

8.1

Company rating: 8.1 out of 10

Based on 470 frontline employees who took The Breakroom Quiz

47th of 142 rated banks

Job description


Machine Learning and Artificial Intelligence play a critical role in transforming Consumer and Community Banking Operations. The ability to utilize data in meaningful ways allows us to develop solutions which both our customers and employees can benefit from. Customers expect tailored servicing and Chase is looking to deliver personalization to meet their needs. This is powered by high-quality annotated data and detailed annotation schemes that are the backbone of impactful Artificial Intelligence/Machine Learning ( AI/ML)L algorithms and applications.
As a Data Domain Architect Lead within the Data Annotation team , you will use your domain expertise and people-leading experience to partner your team closely with teams in Data Science, Analytics, and Engineering to develop machine learning solutions. This will involve the collection, curation, annotation, enrichment, and validation of data and the development of taxonomies and other linguistic resources to help train machine learning models, drive insight, analysis, and possible content creation.
Job responsibilities
  • Manage and coach a team of Machine Learning Data Domain analysts to support data annotation and label data/content using annotation tools and analysis
  • Partner with leads in Data Science, Engineering, and Analytics to develop strategies to optimize training data for machine learning models
  • Lead efforts to identify patterns and trends in conversational data through Natural Language Processing and/or other computational linguistic approaches
  • Collaborate with stakeholders on evaluating the quality of machine learning classification and other output
  • Actively contribute to the team's continuous learning mindset by bringing in new ideas and perspectives that stretch the thinking of the group

Required qualifications, capabilities, and skills
  • 6+ years of related experience in development of machine learning solutions
  • 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; i.e., data warehousing, data processing, data quality concepts, Business Intelligence tools and analytical tools, unstructured data, machine learning
  • Excellent analytical and problem-solving skills and the ability to pay close attention to detail
  • Experience using Python in working with and analyzing large real-world datasets
  • Working knowledge of information and data retrieval
  • Working knowledge of machine learning and artificial intelligence paradigms and libraries
  • Familiar with Large Language Models (LLMs) and prompt engineering

Preferred qualifications, capabilities, and skills
  • Masters or PhD in a related field, or Bachelors
  • Technical understanding of common relational database systems; i.e., Teradata and Oracle
  • Excellent command of the Structured Query Language (SQL)
  • Knowledge of SAS or Scala, and Python languages
  • Knowledge of Advanced Statistics
  • Advanced analytical thinking and problem-solving skills
  • Strong interpersonal & communication skills

About Us
Chase is a leading financial services firm, helping nearly half of America's households and small businesses achieve their financial goals through a broad range of financial products. Our mission is to create engaged, lifelong relationships and put our customers at the heart of everything we do. We also help small businesses, nonprofits and cities grow, delivering solutions to solve all their financial needs.
We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
Equal Opportunity Employer/Disability/Veterans
About the Team
Our Consumer & Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We're proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions - all while ranking first in customer satisfaction.
The CCB Data & Analytics team responsibly leverages data across Chase to build competitive advantages for the businesses while providing value and protection for customers. The team encompasses a variety of disciplines from data governance and strategy to reporting, data science and machine learning. We have a strong partnership with Technology, which provides cutting edge data and analytics infrastructure. The team powers Chase with insights to create the best customer and business outcomes.

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