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Data Labelling Jobs in McKinney, TX (NOW HIRING)

Expert Technology Services

Data Annotator

Irving, TX · On-site

$109K - $132K/yr

Required Skills & Qualifications: - 1+ years of experience in data annotation, labeling, or QA for computer vision, robotics, or autonomous systems. - Experience with 3D spatial data (LiDAR, point ...

Vailexa

Lead Data Security Architect

Plano, TX

The emphasis is on supporting the client through the work required to classify, tag, label, prioritize, and remediate data security findings in a structured way. This role works alongside the client ...

Waabi

Senior Software Engineer, Auto Labelling

Dallas, TX · On-site +1

$170K - $220K/yr

... labelling system leveraging computer vision, and machine learning. - Manage the end-to-end ... Bonus/nice to have: - Familiarity with 3D data (LIDAR/Point Clouds) and multi-modal sensor fusion ...

Waabi

Senior Software Engineer, Auto Labelling

Dallas, TX · On-site +1

$170K - $220K/yr

... labelling system leveraging computer vision, and machine learning. - Manage the end-to-end ... Bonus/nice to have: - Familiarity with 3D data (LIDAR/Point Clouds) and multi-modal sensor fusion ...

Waabi

Senior Software Engineer, Auto Labelling

Dallas, TX · On-site +1

$170K - $220K/yr

... labelling system leveraging computer vision, and machine learning. - Manage the end-to-end ... Bonus/nice to have: - Familiarity with 3D data (LIDAR/Point Clouds) and multi-modal sensor fusion ...

CSW Industrials

ERP Data Specialist

Rockwall, TX · On-site

Update and maintain data across JDE and connected systems (EBT, palletizers, labelers, Lisam). * Ensure data consistency and resolve discrepancies across systems. Data Governance & Quality * Enforce ...

Accenture

Data Protection, Manager

Dallas, TX · On-site

$150K - $178K/yr

Design and implement Microsoft Purview solutions (e.g., sensitivity labeling strategies, advanced DLP policies/integrations, Purview DSPM, data lifecycle/retention controls). * Perform threat mapping ...

Accenture

Data Protection, Manager

Irving, TX · On-site

$150K - $178K/yr

Design and implement Microsoft Purview solutions (e.g., sensitivity labeling strategies, advanced DLP policies/integrations, Purview DSPM, data lifecycle/retention controls). * Perform threat mapping ...

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All JobsData Labelling JobsData Labelling Jobs in McKinney, TX

Data Labelling information

See McKinney, TX salary details

$42.7K

$153.1K

$226K

How much do data labelling jobs pay per year?

As of Aug 24, 2026, the average yearly pay for data labelling in McKinney, TX is $153,143.00, according to ZipRecruiter salary data. Most workers in this role earn between $123,900.00 and $157,800.00 per year, depending on experience, location, and employer.

What is a data labelling?

A Data Labelling job involves annotating data, such as text, images, audio, or video, to help train machine learning models. Labelers categorize or tag data by following specific guidelines to ensure accuracy and consistency. This process is essential for improving AI applications, including image recognition, natural language processing, and autonomous systems. Attention to detail and adherence to instructions are key skills required for this role.

What are the typical daily responsibilities of a data labelling professional?

Data Labelling professionals are generally responsible for reviewing and accurately annotating large volumes of data—such as images, audio, video, or text—to support machine learning and AI projects. This often involves using specialized labeling platforms and following detailed guidelines provided by data scientists or project managers. You may also participate in regular team meetings to discuss quality standards or address ambiguities in data, and your work is typically reviewed for accuracy before being integrated into training datasets. Collaborating with other data annotators, engineers, and analysts is a common part of the process to ensure consistency and high-quality results.

What are the key skills and qualifications needed to thrive in the data labelling position, and why are they important?

To thrive as a Data Labelling professional, you need strong attention to detail, proficiency with data annotation processes, and a basic understanding of machine learning concepts. Familiarity with annotation tools like Labelbox, Supervisely, or Amazon SageMaker Ground Truth is often required, and some roles may value certifications in data processing or AI fundamentals. Reliability, patience, and the ability to follow precise instructions are important soft skills for success in this position. These skills ensure accurate and consistent data labeling, which is critical for developing effective AI models and maintaining data integrity.

How can I get started in data labeling?

To start in data labeling, gain familiarity with annotation tools and understand the specific data types you'll work with, such as images, text, or audio. Building attention to detail and basic knowledge of machine learning concepts can improve your effectiveness; some roles may require basic computer skills or certifications. Entry-level positions often offer flexible schedules and remote work options.

How much do data labelers make?

Data labelers typically earn between $10 and $20 per hour, depending on experience, complexity of tasks, and the platform they work for. Some may earn higher rates with specialized skills or certifications, especially for complex data annotation tasks involving images, videos, or audio. Pay can vary based on whether the work is freelance, part-time, or full-time, and some roles offer project-based or hourly compensation.

Is data labelling a good career?

Data labelling is a common entry-level role in data annotation and machine learning workflows, often requiring attention to detail and familiarity with labeling tools. It can provide opportunities to develop skills in data management and AI, but typically offers lower pay and limited advancement without additional training or experience.

What are data labeling jobs?

Data labeling jobs involve annotating or tagging data such as images, text, or videos to help machine learning models learn and improve. These roles typically require attention to detail and familiarity with labeling tools or software, and they are often performed remotely with flexible schedules.

What are the most commonly searched types of Data Labelling jobs in McKinney, TX?

The most popular types of Data Labelling jobs in McKinney, TX are:

What are popular job titles related to Data Labelling jobs in McKinney, TX?

For Data Labelling jobs in McKinney, TX, the most frequently searched job titles are:

What job categories do people searching Data Labelling jobs in McKinney, TX look for?

The top searched job categories for Data Labelling jobs in McKinney, TX are:

What cities near McKinney, TX are hiring for Data Labelling jobs?

Cities near McKinney, TX with the most Data Labelling job openings:

Data Labelling jobs near you
Infographic showing various Data Labelling job openings in McKinney, TX as of August 2026, with employment types broken down into 1% As Needed, 78% Full Time, 19% Part Time, and 2% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution, with an average salary of $153,143 per year, or $73.6 per hour.

Data Annotator

Expert Technology Services

Irving, TX • On-site

$109K - $132K/yr

Contractor

Posted 18 days ago

Job description

Job Summary (List Format): Data Annotator & QA Reviewer – Autonomy & Robotics (Mining)
- Perform manual data annotation and quality assurance (QA) review for perception and VLA (Vision-Language-Action) data, including video, images, and multi-sensor machine data.
- Annotate mining site entities (e.g., roads, rock piles, vehicles, personnel, machinery) in both 2D and 3D data formats (LiDAR, radar, video).
- Track heavy equipment trajectories and operational states, including motion paths, articulation, bucket/blade actions, and velocity in challenging mining environments.
- Align and fuse data from various sensors (camera, LiDAR, GPS/GNSS, IMU, CAN bus, payload sensors) to maintain accurate spatial and temporal mapping.
- Decompose mining workflows into structured task sequences, labeling actions, operator/machine intent, causations, and outcomes for autonomous system training.
- Model and annotate causal relationships and site-specific triggers (e.g., environmental changes, equipment reactions) in mining operations.
- Tag and verify outcomes of machine actions, comparing expected vs. actual results (e.g., load success, hazard avoidance, maneuver outcomes).
- Conduct rigorous QA audits of labeled datasets, ensuring high accuracy, semantic consistency, and correct handling of mining-specific edge cases (dust, mud, night, glare, underground).
- Provide feedback and update labeling guidelines based on emerging annotation challenges and edge cases.
- Utilize various labeling platforms (CVAT, Labelbox, Scale AI, Supervisely, V7, Encord, etc.) for high-precision data annotation.
- Collaborate with internal and external teams to maintain data quality standards and continuously improve annotation processes.
Required Skills & Qualifications:
- 1+ years of experience in data annotation, labeling, or QA for computer vision, robotics, or autonomous systems.
- Experience with 3D spatial data (LiDAR, point clouds, depth maps, spatial trajectories, multi-camera feeds).
- Strong attention to detail, especially for complex spatial and environmental scenarios.
- Familiarity with mining operations, heavy equipment, and related safety/operational terminology.
- Technical aptitude with geospatial/sensor data formats (JSON, XML) and labeling tools.
- Ability to breakdown complex workflows into sequenced actions and label accordingly.
- Strong 3D spatial visualization and perception skills.
Desired (Nice to Have):
- Background in Mining Engineering, Robotics, Autonomous Vehicles, or related fields.
- Experience with autonomous haulage systems or industrial robotics VLA models.