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Data Annotation Manager Jobs (NOW HIRING)

TEKsystems

Data Annotation Specialist

Austin, TX · Remote

$25 - $35/hr

Use annotation tools to mark up text, images, or other data according to specific guidelines. Participate in the validation and quality assurance of annotated data to ensure it meets the required ...

Q Analysts

Data Annotation Technician

Kirkland, WA · On-site

Data Annotation Technician Join Q Analysts and become part of a world-class organization. Q ... Q Analysts provides industry-leading managed services that drive Quality for Quality Assurance and ...

Innodata Inc.

$55 - $60/hr

As the Data/Annotation Engineer, you'll be hands-on with the data itself ... You'll administer the annotation toolchain, manage annotation workflows across the corpus, and ...

NEURA Robotics

Your mission & challenges As an AI Data Annotation Specialist, you will operate at the intersection of data ingestion, processing, and machine learning. Your primary responsibility is to design and ...

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How much do data annotation manager jobs pay per year?

As of Sep 13, 2026, the average yearly pay for data annotation manager in the United States is $97,145.00, according to ZipRecruiter salary data. Most workers in this role earn between $66,000.00 and $125,500.00 per year, depending on experience, location, and employer.

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.

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

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.

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 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.

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Data Annotation Manager jobs near you
Infographic showing various Data Annotation Manager job openings in the United States as of September 2026, with employment types broken down into 67% Full Time, and 33% Part Time. Highlights an 100% Remote job distribution, with an average salary of $97,145 per year, or $46.7 per hour.

Data Annotation Engineer

Louisville, KY • On-site

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

Other

Posted 16 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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