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Data Labelling Jobs in Houston, TX (NOW HIRING)

Perform high-precision 3D instance labeling, semantic segmentation, and bounding box annotation on multi-sensor data (LiDAR, Camera, Radar, etc.). • Vectorized Map Annotation: Annotate and edit ...

Be Seen First

We are seeking Voice And Data Technicians to become an integral part of our team! You will design ... Able to terminate, label, test Cat3, Cat5E, Cat6. May know SM/MM Fiber. Punch down 66 and 110 ...

Be Seen First

We are seeking Voice And Data Technicians to become an integral part of our team! You will design ... Able to terminate, label, test Cat3, Cat5E, Cat6. May know SM/MM Fiber. Punch down 66 and 110 ...

Perform high-precision 3D instance labeling, semantic segmentation, and bounding box annotation on multi-sensor data (LiDAR, Camera, Radar, etc.). * Vectorized Map Annotation: Annotate and edit high ...

Perform high-precision 3D instance labeling, semantic segmentation, and bounding box annotation on multi-sensor data (LiDAR, Camera, Radar, etc.). * Vectorized Map Annotation: Annotate and edit high ...

Data Protection Consultant

Houston, TX · On-site

$112K - $133K/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 ...

We are looking for a highly skilled and motivated Data Center Deployment Lead I to join our team at ... labeling, terminations -- and correct mistakes in the field immediately Ensure all team members ...

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Data Labelling information

See Houston, TX salary details

$43.9K

$157.6K

$232.5K

How much do data labelling jobs pay per year?

As of Jul 15, 2026, the average yearly pay for data labelling in Houston, TX is $157,588.00, according to ZipRecruiter salary data. Most workers in this role earn between $127,500.00 and $162,300.00 per year, depending on experience, location, and employer.

What does a data labeler do?

A data labeler is responsible for annotating and categorizing data such as images, videos, or text to help train machine learning models. They use tools and guidelines to ensure accurate labeling, which is essential for developing reliable AI systems. Attention to detail and understanding of the data are important for this role.

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 offer flexible schedules and opportunities to develop skills in AI and data management, but typically involves repetitive tasks and lower pay compared to more advanced tech roles.

What is a Data Labelling job?

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 is the job description of data labeling?

Data labeling involves annotating or tagging data such as images, text, or videos to help machine learning models understand and learn from the data. The role requires attention to detail, familiarity with labeling tools, and adherence to guidelines to ensure high-quality annotations for AI training. It is often performed remotely and may involve repetitive tasks with a focus on accuracy.

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 like Labelbox or CVAT and understand data privacy requirements. Basic skills in image, text, or audio annotation are helpful, and some roles may require attention to detail and the ability to follow guidelines. Entry-level positions often provide training, making it accessible for beginners.
What are the most commonly searched types of Data Labelling jobs in Houston, TX? The most popular types of Data Labelling jobs in Houston, TX are:
What job categories do people searching Data Labelling jobs in Houston, TX look for? The top searched job categories for Data Labelling jobs in Houston, TX are:
What cities near Houston, TX are hiring for Data Labelling jobs? Cities near Houston, TX with the most Data Labelling job openings:
Infographic showing various Data Labelling job openings in Houston, TX as of July 2026, with employment types broken down into 1% As Needed, 85% Full Time, 12% Part Time, and 2% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $157,588 per year, or $75.8 per hour.

Data Annotation Specialist

Bot Auto

Houston, TX • On-site

Full-time

Re-posted 23 days ago


Job description

Job Summary:
Bot Auto is revolutionizing the transportation of goods with autonomous trucks. The Data Annotation Specialist will be responsible for creating, refining, and validating ground-truth data for the company's perception and mapping stacks.
Responsibilities:
• 3D Perception Annotations: Perform high-precision 3D instance labeling, semantic segmentation, and bounding box annotation on multi-sensor data (LiDAR, Camera, Radar, etc.).
• Vectorized Map Annotation: Annotate and edit high-definition vectorized map elements, including lane geometries, traffic signals, and regulatory features.
• Human-in-the-Loop Refinement: Examine and refine autolabeling results, identifying edge cases where automated systems may falter.
• Quality Assurance: Review auto-generated labels against strict pass/fail criteria to ensure only the highest quality data enters our training pipelines.
• Cross-Functional Feedback: Collaborate closely with Machine Learning and Mapping engineers to provide feedback on labeling guidelines and tool improvements.
• Documentation: Assist in maintaining clear and concise labeling SOPs (Standard Operating Procedures) to ensure consistency across the data operations team.
Qualifications:
Required:
• Extreme Attention to Detail: A proven track record of identifying small discrepancies in complex datasets or visual environments.
• Communication Skills: Outstanding verbal and written communication abilities; ability to clearly explain complex visual scenarios to technical teams.
• Technical Aptitude: Comfortable working with proprietary software tools and navigating 3D environments (Point Clouds/Bird’s Eye View).
• Adaptability: Ability to thrive in a fast-paced startup environment and pivot between perception and mapping tasks as project priorities shift.
• Professionalism: High degree of self-discipline and the ability to work independently while meeting rigorous quality and throughput targets.
Preferred:
• Prior experience in data annotation for autonomous driving, robotics, or computer vision.
• Understanding of autonomous vehicle sensor modalities (LiDAR, Radar, Cameras).
• Experience with 3D labeling tools.
• Familiarity with HD maps.
Company:
Transforming American Transportation with Autonomous Trucks Founded in 2023, the company is headquartered in Houston, USA, with a team of 51-200 employees. The company is currently Growth Stage.