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Data Annotation Manager Jobs in Raleigh, NC (NOW HIRING)

... image annotation projects. In this role, you will review images and accurately assign the ... Other Duties May be required to perform other duties as assigned by management, which are ...

New

... cleansing, preparation, annotation, feature engineering, exploratory analysis, and model ... Advises senior management on technical strategy. * Regularly provides guidance, training, and ...

... cleansing, preparation, annotation, feature engineering, exploratory analysis, and model ... Advises senior management on technical strategy. * Regularly provides guidance, training, and ...

Data Annotation Manager information

See Raleigh, NC salary details

$30.1K

$94.4K

$167.2K

How much do data annotation manager jobs pay per year?

As of Jul 22, 2026, the average yearly pay for data annotation manager in Raleigh, NC is $94,427.00, according to ZipRecruiter salary data. Most workers in this role earn between $64,200.00 and $122,000.00 per year, depending on experience, location, and employer.

What is the salary of data annotation manager?

The salary of a data annotation manager typically ranges from $60,000 to $120,000 annually, depending on experience, location, and company size. Senior roles or those in high-cost areas may offer higher compensation, and familiarity with annotation tools and team management can influence pay levels.

How much do data annotation project managers make?

Data annotation project managers typically earn between $60,000 and $100,000 annually, depending on experience, location, and company size. They oversee annotation teams, coordinate workflows, and ensure quality standards are met, often requiring familiarity with annotation tools and project management skills.

What are some common challenges faced by Data Annotation Managers, and how can they be addressed?

Data Annotation Managers often encounter challenges such as maintaining high annotation quality across large and diverse datasets, managing a distributed team of annotators, and meeting tight project deadlines. To address these, it's important to implement robust quality assurance processes, provide ongoing training for annotators, and establish clear communication channels. Leveraging annotation tools with built-in validation features can also help ensure consistency and accuracy. Building a positive and collaborative team environment further contributes to better outcomes and workflow efficiency.

What does a Data Annotation Manager do?

A Data Annotation Manager oversees the process of labeling and categorizing data used to train machine learning models. They manage teams of annotators, ensure data quality, develop annotation guidelines, and coordinate with data scientists to meet project requirements. Their role is critical in maintaining high standards of accuracy and efficiency, as well as ensuring that datasets are properly prepared for AI and machine learning applications.

Does data annotation actually pay well?

Data annotation managers typically earn competitive salaries that reflect their experience and responsibilities, often ranging from entry-level to senior roles. Compensation can vary based on industry, location, and company size, with specialized skills in tools like labeling platforms and quality control often leading to higher pay.

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

To thrive as a Data Annotation Manager, you need expertise in data labeling processes, quality control, and a solid understanding of machine learning concepts, usually backed by a degree in computer science or a related field. Proficiency with annotation tools such as Labelbox, Supervisely, or CVAT, as well as experience with project management systems, is commonly required. Exceptional leadership, attention to detail, and strong communication skills help manage teams and ensure high annotation accuracy. These skills are critical for delivering reliable labeled datasets, which are essential for building effective AI and machine learning models.

How hard is it to get hired by data annotation?

Getting hired as a data annotation manager typically requires relevant experience in data labeling, familiarity with annotation tools, and strong organizational skills. The hiring process often involves reviewing previous work, technical assessments, and demonstrating attention to detail, with opportunities available in companies that outsource data labeling tasks.

What is the difference between Data Annotation Manager vs Data Labeling Specialist?

AspectData Annotation ManagerData Labeling Specialist
CredentialsBachelor's degree in related field, experience in data managementHigh school diploma or equivalent, training in labeling tools
Work EnvironmentTeam management, project oversight, collaboration with data scientistsHands-on labeling work, using annotation tools, focused on data tagging
Industry UsageUsed in AI/ML projects for overseeing annotation teamsPerforms the actual data labeling tasks in machine learning workflows

The Data Annotation Manager oversees the entire annotation process, managing teams and ensuring quality, while the Data Labeling Specialist focuses on executing labeling tasks. Both roles are essential in AI/ML data preparation but differ in responsibilities and scope.

What are the most commonly searched types of Data Annotation jobs in Raleigh, NC? The most popular types of Data Annotation jobs in Raleigh, NC are:
What are popular job titles related to Data Annotation Manager jobs in Raleigh, NC? For Data Annotation Manager jobs in Raleigh, NC, the most frequently searched job titles are:
What job categories do people searching Data Annotation Manager jobs in Raleigh, NC look for? The top searched job categories for Data Annotation Manager jobs in Raleigh, NC are:
What cities near Raleigh, NC are hiring for Data Annotation Manager jobs? Cities near Raleigh, NC with the most Data Annotation Manager job openings:
Infographic showing various Data Annotation Manager job openings in Raleigh, NC as of July 2026, with employment types broken down into 2% Locum Tenens, 36% Full Time, 25% Part Time, 1% Contract, 35% Nights, and 1% Summer. Highlights an 56% Physical, 1% Hybrid, and 43% Remote job distribution, with an average salary of $94,427 per year, or $45.4 per hour.
Data Labeling Specialist

Data Labeling Specialist

Vadum Inc

Raleigh, NC โ€ข On-site

Other

Posted yesterday


Job description

Description

ย We are seeking a detail-oriented Data Labeling Specialist temporarily (6 months) to support image annotation projects. In this role, you will review images and accurately assign the appropriate labels based on provided guidelines.ย 


ย Job Duties and Responsibilities


Review and analyze images.

Apply accurate labels according to project instructions and quality standards.

Maintain high levels of accuracy and consistency across assigned tasks.

Follow labeling guidelines and update annotations as needed based on feedback.

Meet productivity and quality targets while ensuring attention to detail.


Other Duties

May be required to perform other duties as assigned by management, which are reasonably within the scope of the position.

Requirements

  • Strong logical thinking and problem-solving skills.
  • Ability to visually identify objects and distinguish fine details in images.
  • Excellent attention to detail and accuracy.
  • Ability to follow detailed instructions and labeling guidelines.
  • Basic computer skills and ability to work independently.
  • Previous experience in data labeling, image annotation, or quality assurance.
  • Familiarity with AI, machine learning, or annotation tools is a plus, but not required.

Physical Demands

  • Work is sedentary and usually accomplished while sitting at a desk and working on a computer.
  • Some walking and standing may occur in the course of a normal workday to attend meetings.
  • Items carried typically are light objects weighing less than 15 lbs. such as a notebook, laptop, backpack.
  • Lifting moderately heavy objects is not normally required.
  • Work requires ability to operate standard office and computer equipment.

Work Environment

  • Work is performed in an office environment.


Travel

  • None.