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Manager Annotation Jobs (NOW HIRING)

Innodata Inc.

Data & Annotation Engineer

Washington, DC · On-site

$55 - $60/hr

You'll administer the annotation toolchain, manage annotation workflows across the corpus, and produce the per-dataset documentation that feeds our governance framework. You'll work with the AI ...

Innodata Inc.

$55 - $60/hr

You'll administer the annotation toolchain, manage annotation workflows across the corpus, and produce the per-dataset documentation that feeds our governance framework. You'll work with the AI ...

Talent Groups

Data Annotation Engineer

Louisville, KY · On-site

We are looking for an Annotation Program Lead to manage our AI Quality Annotation Program. This individual will oversee the operational execution of human review activities that establish the gold ...

EVB

Video Annotation Specialist

Demonstrated time management and self-organization abilities for independent project participation. * Familiarity with video annotation tools and software platforms. * Background in AI training ...

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Manager Annotation information

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$24.5K

$59.5K

$116K

How much do manager annotation jobs pay per year?

As of Sep 15, 2026, the average yearly pay for manager annotation in the United States is $59,525.00, according to ZipRecruiter salary data. Most workers in this role earn between $42,000.00 and $68,500.00 per year, depending on experience, location, and employer.

What is a manager annotation?

Manager Annotation jobs involve overseeing teams responsible for labeling and annotating data, which is critical for training machine learning models. These managers coordinate workflows, ensure quality control, and facilitate communication between annotators and data scientists. They are responsible for setting guidelines, managing deadlines, and addressing any issues that arise during the annotation process. Manager Annotation roles often require a combination of leadership skills and an understanding of data annotation tools and processes.

What are the key skills and qualifications needed to thrive as a manager annotation?

To thrive as a Manager Annotation, you need expertise in data annotation processes, team leadership, and quality assurance, often supported by a relevant degree and experience in data labeling or AI/ML projects. Familiarity with annotation tools (such as Labelbox, Supervisely, or AWS SageMaker Ground Truth), project management software, and sometimes certifications in project management or data science are valuable. Strong communication, problem-solving abilities, and attention to detail help ensure effective team coordination and high-quality data outputs. These skills are crucial for delivering accurate training data, meeting project deadlines, and supporting the success of machine learning initiatives.

What are some common challenges faced by a manager annotation and how can they be addressed?

A Manager Annotation often encounters challenges such as ensuring high-quality data labeling, managing tight project deadlines, and maintaining effective communication across diverse annotation teams. Balancing quality control with efficiency can be demanding, especially when working with large datasets or remote teams. To address these challenges, it is helpful to establish clear annotation guidelines, implement robust quality assurance processes, and foster open communication channels for feedback and support. Regular training and performance reviews also play a key role in maintaining team standards and project consistency.

What is the difference between Manager Annotation vs Data Annotator?

AspectManager AnnotationData Annotator
Required CredentialsHigh school diploma or equivalent; experience in data labeling; leadership skillsHigh school diploma or equivalent; attention to detail; basic computer skills
Work EnvironmentOffice or remote management setting overseeing annotation teamsRemote or on-site data labeling tasks
Employer & Industry UsageTech companies, AI firms, data service providersAI, machine learning, data processing companies

The main difference is that a Manager Annotation oversees annotation teams and manages projects, requiring leadership and management skills, while a Data Annotator performs the actual data labeling work, focusing on accuracy and attention to detail. Managers coordinate workflows, whereas Annotators execute labeling tasks.

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Manager Annotation jobs near you
Infographic showing various Manager Annotation job openings in the United States as of September 2026, with employment types broken down into 87% Full Time, 12% Part Time, and 1% Contract. Highlights an 79% Physical, 2% Hybrid, and 19% Remote job distribution, with an average salary of $59,525 per year, or $28.6 per hour.

Data Annotation Engineer

Louisville, KY • On-site

Tanisha Systems
1 - 5K employees
Learn more about Tanisha Systemsexternal

Other

Posted 18 days ago

Job description

Data Annotation Engineer Location - Louisville, Kentucky (Day 1 onsite) Pay Rate: Market- based on experience We are looking for an Annotation Program Lead to manage our AI Quality Annotation Program. This individual will oversee the operational execution of human review activities that establish the gold-standard datasets used to measure conversational AI performance, safety, and compliance. The ideal candidate combines strong program management skills with experience in quality assurance, data annotation operations, and stakeholder engagement. Lead the day-to-day operation of the AI annotation program. Manage a team of annotators responsible for reviewing customer conversations and AI interactions. Develop annotation guidelines, procedures, and quality standards. Establish calibration programs and quality assurance processes to ensure consistency across reviewers. Partner with Data Scientists to create and maintain gold-standard datasets. Monitor annotation accuracy, throughput, and quality metrics. Coordinate reporting and deliverables for Legal, Compliance, Responsible AI, and executive stakeholders. Manage annotation workflows and tooling including setting up annotation jobs, running data processing scripts, and testing annotation UIs for quality before job launch. Plan capacity requirements to support seasonal increases in review volume. Support future expansion into multilingual evaluation programs. Identify process improvements that increase efficiency and annotation quality. Bachelor's degree or equivalent experience in Linguistics/Psychology. 5+ years of experience in program management, operations, quality assurance, data labeling, or related fields. Experience leading teams and managing operational workflows. Strong organizational and stakeholder management skills. Ability to analyze quality metrics and drive continuous improvement initiatives. Excellent written and verbal communication skills. Familiarity with Python/R, SQL and Excel. Should be familiar with running scripts on language data. Strong organizational and stakeholder management skills. Ability to analyze quality metrics and drive continuous improvement initiatives. Excellent written and verbal communication skills. Familiarity with Python/R, SQL and Excel. Should be familiar with running scripts on language data. Experience supporting AI, machine learning, or data annotation programs. Familiarity with Responsible AI, compliance, legal review, or governance processes. Experience developing operational standards and quality frameworks. Experience managing vendor or contractor resources.

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