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Full Time Data Annotation Tech Jobs (NOW HIRING)

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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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Full Time Data Annotation Tech information

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$12

$22

$34

How much do full time data annotation tech jobs pay per hour?

As of Jul 16, 2026, the average hourly pay for full time 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.

How much does a data annotation tech make per hour?

A full-time data annotation technician typically earns between $12 and $20 per hour, depending on experience, location, and the complexity of annotation tasks. Many roles require attention to detail and familiarity with annotation tools or platforms.

Can you do data annotation full time?

Full-time data annotation roles are available and typically involve working set hours, often 40 hours per week. These positions may require familiarity with annotation tools and attention to detail, and they often offer consistent schedules and remote or on-site options.

How hard is it to get hired by data annotation?

Getting hired as a full-time data annotation technician typically requires basic computer skills, attention to detail, and sometimes familiarity with annotation tools or platforms. The hiring process is generally straightforward, with many companies offering entry-level positions that do not require extensive experience or certifications.

How does a Full Time Data Annotation Tech typically collaborate with data scientists and engineers on projects?

As a Full Time Data Annotation Tech, you will regularly work alongside data scientists and engineers to ensure the accuracy and quality of labeled datasets used for machine learning models. Collaboration often involves attending project meetings to clarify annotation guidelines, providing feedback on ambiguous data cases, and updating annotation processes based on team input. Clear communication is essential, as your work directly impacts model performance and downstream analytics. This team-oriented environment fosters learning and provides insight into broader AI development workflows.

What are Full Time Data Annotation Techs?

Full Time Data Annotation Techs are professionals responsible for labeling and categorizing data used to train machine learning models. They examine various types of data, such as images, text, or audio, and apply specific tags or annotations according to project guidelines. Their work is essential in ensuring the accuracy of artificial intelligence systems by providing high-quality, structured datasets. Full-time positions typically involve working standard business hours and may require familiarity with specialized annotation tools and attention to detail.

What are the key skills and qualifications needed to thrive as a Full Time Data Annotation Tech, and why are they important?

To thrive as a Full Time Data Annotation Tech, you need strong attention to detail, basic data management skills, and familiarity with data labeling practices, typically supported by a high school diploma or equivalent. Experience with annotation tools (such as Labelbox, Supervisely, or similar platforms) and basic proficiency in spreadsheet or database systems are commonly required. Reliability, consistency, and effective communication are crucial soft skills for quality assurance and collaboration with data teams. These skills and qualities are essential to ensure the accuracy and efficiency of annotated datasets, which directly impact the performance of machine learning models.

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

AspectFull Time Data Annotation TechData Labeling Specialist
CredentialsBasic computer skills, attention to detailSimilar credentials, often with training in labeling tools
Work EnvironmentOffice or remote, collaborative teamsRemote or on-site, focused on labeling tasks
Industry UsageAI, machine learning, tech companiesAI, autonomous vehicles, healthcare
Job FocusAnnotating data for machine learning modelsLabeling data to improve AI accuracy

Both roles involve data annotation and labeling, often requiring similar skills and working environments. The main difference lies in job titles used by employers and the scope of responsibilities, with 'Full Time Data Annotation Tech' emphasizing a broader technical role, while 'Data Labeling Specialist' may focus more on specific labeling tasks.

Can you make a living off data annotation?

Full Time Data Annotation Tech roles can provide a stable income, especially with consistent work and experience. However, pay rates vary depending on the employer, location, and complexity of tasks, and many positions are part-time or freelance, which may affect earning potential.
More about Full Time Data Annotation Tech jobs
What cities are hiring for Full Time Data Annotation Tech jobs? Cities with the most Full Time 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 Full Time Data Annotation Tech jobs? States with the most job openings for Full Time Data Annotation Tech jobs include:
Infographic showing various Full Time 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

Data Domain Architect Lead

JPMorgan Chase & Co

Wilmington, DE • On-site

Full-time

Medical, Retirement

Re-posted 12 days ago


JPMorgan Chase & Co. rating

8.0

Company rating: 8.0 out of 10

Based on 491 frontline employees who took The Breakroom Quiz

58th of 149 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

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

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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