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Online Data Labelling Jobs (NOW HIRING)

Online Labels Group

Order Build Associate

Sanford, FL · On-site

$17/hr

Watch this video to learn more about the culture here at Online Labels Group! Overview: The Order ... All chemical use is managed in accordance with Safety Data Sheets (SDS) and company safety ...

QuinStreet

Data Analyst

Foster City, CA · Remote

$85K - $100K/yr

... online marketplaces that match searchers and "research and compare" consumers with brands ... We run these virtual- and private-label marketplaces in one of the nation's largest media networks.

Technica Corporation

Senior Cloud Engineer

Dulles, VA · On-site +1

$105K - $144K/yr

... Online, Teams, Azure-hosted infrastructure, VDI integration, endpoint compliance, data labeling, DLP, secure collaboration, and CUI/manufacturing data protection. The Senior Cloud Engineer will work ...

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Online Data Labelling information

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$46K

$165K

$243.5K

How much do online data labelling jobs pay per year?

As of Jun 21, 2026, the average yearly pay for online data labelling in the United States is $165,018.00, according to ZipRecruiter salary data. Most workers in this role earn between $133,500.00 and $170,000.00 per year, depending on experience, location, and employer.

What is the difference between Online Data Labelling vs Data Annotation?

AspectOnline Data LabellingData Annotation
CredentialsBasic computer skills, attention to detailSimilar, often no formal certification required
Work EnvironmentRemote, flexibleRemote or in-office, depending on project
Industry UsageCommon in AI/ML data preparationUsed across AI, computer vision, NLP projects
Search IntentOnline Data Labelling vs Data Annotation

Online Data Labelling and Data Annotation are closely related roles in AI data preparation. While both involve labeling data for machine learning, Online Data Labelling often emphasizes quick, online tasks, whereas Data Annotation may include more detailed, specialized labeling. Both roles are essential in training AI models and share similar skills and work environments.

What is online data labelling?

Online data labelling is the process of tagging or annotating data—such as images, text, or audio—using digital tools to make it understandable for machine learning algorithms. Data labelers review raw data and apply predefined labels to help train artificial intelligence systems, enabling them to recognize patterns and make predictions. This work is essential for improving the accuracy and performance of AI models in various applications, such as image recognition, natural language processing, and autonomous vehicles. Online data labelling jobs are often remote and require attention to detail, consistency, and sometimes domain-specific knowledge.

What are some common challenges faced by online data labelers, and how can they be managed effectively?

Online data labelers often encounter challenges such as repetitive tasks, strict accuracy requirements, and tight deadlines. Maintaining high attention to detail is crucial, as even small errors can impact the quality of machine learning models. To manage these challenges, it's helpful to take regular breaks, use productivity tools, and communicate any ambiguities or unclear instructions with supervisors or team leads. Many organizations also offer support channels and quality assurance feedback to help labelers continuously improve their work.

What are the key skills and qualifications needed to thrive as an Online Data Labeller, and why are they important?

To excel as an Online Data Labeller, you need strong attention to detail, basic data handling skills, and familiarity with data annotation protocols, often requiring at least a high school diploma. Proficiency with data labelling platforms such as Labelbox, Supervisely, or Scale AI, and sometimes knowledge of spreadsheet tools, is typically necessary. Reliability, consistency, and the ability to follow detailed guidelines make individuals stand out in this role. These skills ensure high-quality, accurately labelled datasets that are critical for training effective AI and machine learning models.
More about Online Data Labelling jobs
What cities are hiring for Online Data Labelling jobs? Cities with the most Online Data Labelling job openings:
What are the most commonly searched types of Data Labelling jobs? The most popular types of Data Labelling jobs are:
What states have the most Online Data Labelling jobs? States with the most job openings for Online Data Labelling jobs include:
Online Data Labelling jobs near you
Infographic showing various Online Data Labelling job openings in the United States as of June 2026, with employment types broken down into 84% Full Time, and 16% Part Time. Highlights an 78% Physical, 1% Hybrid, and 21% Remote job distribution, with an average salary of $165,018 per year, or $79.3 per hour.

Cyber Data Analytics Engineer - PRIME, Hybrid - TS/SCI with Security Clearance

SRC

Columbia, MD • Hybrid

Other

Medical, Retirement, PTO

Posted 4 days ago

Job description

Who We Are Stanley Reid is a specialized recruiting firm connecting top contractors with exciting IC/DoD opportunities. We're dedicated to a personalized, stress-free job search, matching your unique skills and goals with the perfect role. About Our Client Our client is a woman-owned small business supporting critical missions in the IC/DoD.

They specialize in cybersecurity, software development, data science, and cloud migration. Enjoy a close-knit team and exceptional benefits, including fully-paid medical, 4 weeks PTO, 6% 401k match, and over $5k for training. The Role Our client is seeking a Data Profiler to support the research, normalization, and correlation of mission-critical data sets.

In this role, you will leverage SIEM platforms to author complex queries and develop analytics that drive data integrity. You will work across a variety of cyber data sources to perform extraction, custom translation, and loading, ensuring data is properly prepped and labeled for high-level analytics. This position is ideal for a detail-oriented professional who can navigate technical complexities and work effectively in both independent and team environments.

What You'll Bring Experience: Technical BS + 9 years of total relevant experience (3 years specific to the role plus 6 years in similar data analytical positions; 4 years of additional experience may substitute for a degree). Technical Skills: Proficiency with SIEM tools (Splunk, Elastic) and the ability to author complex queries (SPL, SQL, Kibana, or Sigma Rules). Core Competencies: Fluency in ETL processes, custom translation development, and data labeling.

Domain Knowledge: Technical experience in cyber data analysis, including continuous monitoring, intelligence, and reporting. Desired Extras: Familiarity with the OSI model, common network protocols, and various log formats (JSON, XML). Experience with Jupyter notebooks or Big Data Platforms (BDP/JCC2) is a plus.

Certifications: DoD IAT II or higher (Sec+, etc) required for consideration. *Please note: Applicants may be required to complete a coding challenge during the interview process per customer requirements. Clearance Requirements Active TS/SCI is required; CI poly preferred.

Please note, you must have the required clearance for consideration; under-cleared applicants will not receive a response. Location San Antonio, TX; Columbia, MD; or Sterling, VA (Hybrid) Ready for Next Steps? We encourage you to apply and connect with us even if a direct match isn't currently listed.

Apply online at https://careers.stanleyreid.com/ or contact our MD team for more info: , . Please Note Due to high application volume, we are unable to confirm receipt of submissions or provide updates. We will contact you directly if there is a match.

Opportunities change frequently; We cannot guarantee availability. Posted on 03/17/2026

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