ZipRecruiter

Log In

1

Seasonal Data Annotation Tech Jobs (NOW HIRING)

JPMorganChase

Data Domain Architect Lead

Wilmington, DE · On-site

... 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 ...

J.P. Morgan

Data Domain Architect Lead

Columbus, OH

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 ...

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

Des Moines, IA · 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

Miami, FL · 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

Louisville, KY

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

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

New York, NY

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

New York, NY

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 · 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 ...

next page

Showing results 1-20

All JobsData Annotation Tech JobsSeasonal Data Annotation Tech Jobs

Seasonal Data Annotation Tech information

See salary details

$12

$22

$34

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

As of Jul 15, 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.
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 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 Domain Architect Lead

JPMorganChase

Wilmington, DE • On-site

Full-time

Re-posted 11 days ago

Job description

Job Summary:
JPMorganChase is a leading financial services firm, helping nearly half of America’s households and small businesses achieve their financial goals. As a Data Domain Architect Lead, you will manage a team to develop machine learning solutions through data annotation, curation, and validation while collaborating with other teams to optimize training data for machine learning models.
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
Qualifications:
Required:
• 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:
• 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
Company:
With a history tracing its roots to 1799 in New York City, JPMorganChase is one of the world's oldest, largest, and best-known financial institutions—carrying forth the innovative spirit of our heritage firms in global operations across 100 markets. Founded in 2000, the company is headquartered in New York, USA, with a team of 10001+ employees. The company is currently Late Stage.

Apply