Data Labeling Specialist Jobs
Data Labeling Specialist jobs are open from entry-level to senior across AI development, autonomous vehicles, healthcare tech, and enterprise software, with specializations in image annotation, text classification, and audio transcription. Find a role that fits below and apply directly.
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NextGen Federal Systems is seeking a detail-oriented Mid-Level Data Labeling Specialist to support Artificial Intelligence Operations (AIOPS) initiatives within the Next Generation Command and Control (NGC2) environment. This role will focus on preparing, annotating, categorizing, and validating structured and unstructured data for use within existing AI platforms and operational applications.
AIOPS supports the operational adoption and use of AI-enabled capabilities across NGC2. Accurate, consistently organized, and traceable data helps ensure these existing platforms can effectively support operational workflows and user requirements.
The ideal candidate will have practical experience in data annotation, data quality assurance, and dataset organization, with the ability to apply defined labeling standards independently. This role requires collaboration with technical personnel, functional subject matter experts, and government stakeholders to clarify data requirements and resolve quality issues.
Key Responsibilities
- Annotate and classify operational datasets, including specific modalities, using approved taxonomies, metadata standards, and task-specific instructions.
- Prepare and organize labeled datasets for use within existing AI platforms and applications.
- Review annotations for accuracy, completeness, consistency, and adherence to approved labeling conventions.
- Identify, document, and resolve data discrepancies, ambiguous records, duplicate entries, and inconsistent labels; elevate unresolved cases to appropriate subject matter experts.
- Coordinate with technical teams and functional subject matter experts to clarify labeling criteria and data interpretation.
- Perform first and second-pass quality reviews using defined sampling plans, acceptance criteria, and annotation-agreement measures; document findings and complete required rework.
- Maintain data labeling records, change history, quality findings, and supporting documentation to preserve traceability.
- Support the refinement of annotation instructions, review checklists, and repeatable data quality workflows.
- Handle data in accordance with applicable government security, access, and information management requirements.
Required Qualifications
- Bachelor’s degree in Information Systems, Data Analytics, Computer Science, or a related discipline; equivalent relevant experience may be considered.
- 3–5 years of relevant experience in data labeling, data annotation, data quality assurance, data management, or comparable data operations.
- Demonstrated experience reviewing, categorizing, and validating structured or unstructured datasets.
- Ability to apply labeling guidelines, metadata conventions, and documented quality standards consistently.
- Experience identifying data discrepancies and documenting corrective actions.
- Proficiency with spreadsheet applications and common data organization tools.
- Strong attention to detail, analytical judgment, and organizational skills.
- Ability to work independently while coordinating with technical teams and nontechnical subject matter experts.
- Strong written and verbal communication skills.
- Active Security Clearance Required: Secret or higher
Desired Qualifications
- Experience supporting DoD or other government data operations programs.
- Familiarity with data annotation or labeling platforms such as Label Studio, CVAT, or comparable tools.
- Experience preparing data for use in existing AI-enabled applications or operational analytics platforms.
- Familiarity with metadata management, controlled vocabulary, taxonomies, and dataset versioning.
- Experience with quality sampling, annotation agreement checks, and repeatable data review processes.
- Familiarity with CSV, JSON, SQL, or other common data formats and query tools.
- Experience working in controlled-access or secure government computing environments.
About NextGen:
NextGen Federal Systems is an innovative technology and professional services provider specializing in advanced software solutions and comprehensive mission and business support services. We work in close collaboration with our customers to truly understand their business and mission goals. Our approach is to design, build, implement, and manage solutions that measurably improve our client’s organizational performance. We have established and foster a corporate culture where we:
- Treat employees with fairness and respect regardless of their position, sexual identity, race, or tenure.
- Communicate the importance of our mission and our employees’ contributions to it, ensuring they understand how their job role contributes to the greater good.
- Openly promote and communicate our ideas for change and adaptability.
- Strive to achieve results as an organization.
- Hold employees accountable to their commitments and provide incentives that encourage positive and productive behaviors.
- Value the talents and contributions of our employees as the key factor for our success.
- Create an environment where people can engage at all levels.
- Encourage people to take risks and allow them to make mistakes.
Equal Opportunity Employer/Protected Veterans/Individuals with Disabilities.
RefID: A02x
NextGen Federal Systems is seeking a detail-oriented Mid-Level Data Labeling Specialist to support Artificial Intelligence Operations (AIOPS) initiatives within the Next Generation Command and Control (NGC2) environment. This role will focus on preparing, annotating, categorizing, and validating structured and unstructured data for use within existing AI platforms and operational applications.
AIOPS supports the operational adoption and use of AI-enabled capabilities across NGC2. Accurate, consistently organized, and traceable data helps ensure these existing platforms can effectively support operational workflows and user requirements.
The ideal candidate will have practical experience in data annotation, data quality assurance, and dataset organization, with the ability to apply defined labeling standards independently. This role requires collaboration with technical personnel, functional subject matter experts, and government stakeholders to clarify data requirements and resolve quality issues.
Key Responsibilities
- Annotate and classify operational datasets, including specific modalities, using approved taxonomies, metadata standards, and task-specific instructions.
- Prepare and organize labeled datasets for use within existing AI platforms and applications.
- Review annotations for accuracy, completeness, consistency, and adherence to approved labeling conventions.
- Identify, document, and resolve data discrepancies, ambiguous records, duplicate entries, and inconsistent labels; elevate unresolved cases to appropriate subject matter experts.
- Coordinate with technical teams and functional subject matter experts to clarify labeling criteria and data interpretation.
- Perform first and second-pass quality reviews using defined sampling plans, acceptance criteria, and annotation-agreement measures; document findings and complete required rework.
- Maintain data labeling records, change history, quality findings, and supporting documentation to preserve traceability.
- Support the refinement of annotation instructions, review checklists, and repeatable data quality workflows.
- Handle data in accordance with applicable government security, access, and information management requirements.
Required Qualifications
- Bachelor’s degree in Information Systems, Data Analytics, Computer Science, or a related discipline; equivalent relevant experience may be considered.
- 3–5 years of relevant experience in data labeling, data annotation, data quality assurance, data management, or comparable data operations.
- Demonstrated experience reviewing, categorizing, and validating structured or unstructured datasets.
- Ability to apply labeling guidelines, metadata conventions, and documented quality standards consistently.
- Experience identifying data discrepancies and documenting corrective actions.
- Proficiency with spreadsheet applications and common data organization tools.
- Strong attention to detail, analytical judgment, and organizational skills.
- Ability to work independently while coordinating with technical teams and nontechnical subject matter experts.
- Strong written and verbal communication skills.
- Active Security Clearance Required: Secret or higher
Desired Qualifications
- Experience supporting DoD or other government data operations programs.
- Familiarity with data annotation or labeling platforms such as Label Studio, CVAT, or comparable tools.
- Experience preparing data for use in existing AI-enabled applications or operational analytics platforms.
- Familiarity with metadata management, controlled vocabulary, taxonomies, and dataset versioning.
- Experience with quality sampling, annotation agreement checks, and repeatable data review processes.
- Familiarity with CSV, JSON, SQL, or other common data formats and query tools.
- Experience working in controlled-access or secure government computing environments.
About NextGen:
NextGen Federal Systems is an innovative technology and professional services provider specializing in advanced software solutions and comprehensive mission and business support services. We work in close collaboration with our customers to truly understand their business and mission goals. Our approach is to design, build, implement, and manage solutions that measurably improve our client’s organizational performance. We have established and foster a corporate culture where we:
- Treat employees with fairness and respect regardless of their position, sexual identity, race, or tenure.
- Communicate the importance of our mission and our employees’ contributions to it, ensuring they understand how their job role contributes to the greater good.
- Openly promote and communicate our ideas for change and adaptability.
- Strive to achieve results as an organization.
- Hold employees accountable to their commitments and provide incentives that encourage positive and productive behaviors.
- Value the talents and contributions of our employees as the key factor for our success.
- Create an environment where people can engage at all levels.
- Encourage people to take risks and allow them to make mistakes.
Equal Opportunity Employer/Protected Veterans/Individuals with Disabilities.
RefID: A02x
See All 7 Data Labeling Specialist Jobs
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Find Data Labeling Specialist JobsData Labeling Specialist Job Market
Who's Hiring
Top Industries Hiring
- Technology & Software
What Employers Look For
The qualifications that appear most often in data labeling specialist jobs.
- Experience with image, text, or video annotation using industry-standard labeling platforms
- High attention to detail with demonstrated accuracy rates on structured labeling tasks
- Ability to follow detailed annotation guidelines and ontologies consistently
- Familiarity with quality assurance workflows such as inter-annotator agreement measurement
- Strong written communication skills for flagging ambiguous or edge-case data
- High school diploma or equivalent required, with an associate or bachelor's degree preferred
Tips for Your Data Labeling Specialist Job Search
Tailor your resume to annotation tools
List the specific tools you've used, such as CVAT, Scale AI's platform, Labelbox, or Prodigy. Hiring managers scan for tool familiarity first, and naming the actual software separates your resume from generic applicants claiming 'labeling experience.'
Quantify your labeling throughput and accuracy
Employers care about speed and quality scores, so include concrete output metrics from past work. Phrases like 'maintained a 98% inter-annotator agreement across 10,000 bounding box tasks' land far better than vague references to accuracy or attention to detail.
Apply early to roles that fit
Migrate Mate lists data labeling specialist openings from across the United States in one place, so you can find roles that match and apply directly to each listing.
Filter openings by the data modality
Data labeling roles split sharply by modality: image, video, text, audio, and 3D point cloud. Target postings that match the type of data you've annotated before, since employers in autonomous vehicles or medical imaging want modality-specific experience, not general annotation background.
Prepare a sample annotation for the skills test
Most hiring pipelines include a timed annotation task before the interview stage. Practice your weakest annotation category, review the ontology formats common to your target industry, and check that your hardware setup handles video or point cloud data without lag.
Ask about quality review processes in interviews
Asking how the team measures inter-annotator agreement and resolves edge-case disagreements signals genuine expertise. It shifts the conversation from your willingness to do the work to your understanding of what makes annotation pipelines actually reliable.
Data Labeling Specialist Jobs: Frequently Asked Questions
Which companies are hiring the most data labeling specialists?
The most active employers for data labeling specialists right now are NVIDIA, PlusAI, and Bobyard, and the most openings are in California, Maryland, and Pennsylvania, based on current listings on Migrate Mate as of November 2026. Demand is especially concentrated at AI model developers, autonomous vehicle companies, and enterprise software firms building proprietary training datasets.
How many data labeling specialist jobs are remote?
About 100% of data labeling specialist openings are fully remote or hybrid as of November 2026, reflecting how well the annotation workflow translates to distributed teams. Text and audio classification roles tend to have the highest remote availability, while 3D point cloud and specialized video annotation roles more often require on-site equipment access.
How do you become a data labeling specialist?
Start by learning a free or trial version of a common annotation platform to build hands-on familiarity with bounding boxes, polygons, and entity tagging. Take on freelance or project-based labeling work to accumulate a measurable output history. Document your accuracy rates and task volumes so you have concrete metrics to present. From there, target entry-level roles at AI or machine learning teams where annotation is a core function rather than an afterthought.
Can I get hired as a data labeling specialist with little experience?
Yes, many employers hire data labeling specialists with little direct experience when candidates demonstrate strong attention to detail and can pass a timed annotation skills test. Building a small personal project, such as labeling a public dataset and documenting your accuracy, gives you something concrete to show. Entry-level contract and part-time roles are common starting points and frequently convert to full-time positions after a performance period.
What does the data labeling specialist interview process look like?
Most processes start with a short application review, followed by a take-home or timed annotation task designed to measure your accuracy, consistency, and ability to follow a detailed ontology. If you pass the skills test, you'll typically have a video call with a team lead covering your past labeling experience and how you handle ambiguous or edge-case examples. Some employers add a final conversation about workflow tools and quality assurance practices before extending an offer.
Where can I find and apply to data labeling specialist jobs?
You can find and apply to data labeling specialist jobs on Migrate Mate, which lists current openings from across the United States. Search the roles available, find the ones that match your background and preferred modality, and apply directly to each listing that fits.
See All 7 Data Labeling Specialist Jobs
Find roles that match your experience and apply in just a few clicks.
Find Data Labeling Specialist Jobs