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Data Labeler Jobs in Spring, TX (NOW HIRING)

Bot Auto

Data Annotation Specialist

Houston, TX · On-site

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 ...

Bot Auto

Data Annotation Specialist

Houston, TX

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 ...

Bot Auto

Data Annotation Specialist

Houston, TX · On-site

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 ...

Accenture

Data Protection Consultant

Houston, TX

$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 ...

Introl

Data Center Deployment Lead I

Houston, TX · On-site

$80K - $87K/yr

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 ...

AgileEngine

Taxonomy Analyst

Houston, TX · On-site

Strictly follow established labeling guidelines while exercising sound, independent judgment on ambiguous data points. Must Haves: * You must be authorized to work for ANY employer in the US (e.g ...

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Data Labeler information

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How much do data labeler jobs pay per hour?

As of Jul 12, 2026, the average hourly pay for data labeler in Spring, TX is $12.43, according to ZipRecruiter salary data. Most workers in this role earn between $11.11 and $13.70 per hour, depending on experience, location, and employer.

What is a data labeler job?

A data labeler is responsible for reviewing and annotating data such as images, videos, or text to help train machine learning models. The job typically involves using specialized tools and requires attention to detail and accuracy. Data labelers often work remotely and may need basic computer skills and understanding of data privacy.

What is a Data Labeler job?

A Data Labeler is responsible for annotating and categorizing data, such as images, text, audio, or video, to train machine learning models. This involves tasks like adding tags, marking objects, or verifying data accuracy based on specific guidelines. Their work is essential for improving AI models in areas like speech recognition, computer vision, and natural language processing. Attention to detail and accuracy are crucial in this role.

How much are data labelers paid?

Data labelers typically earn between $10 and $20 per hour, depending on experience, location, and the complexity of the labeling tasks. Many positions are remote and may offer flexible schedules, with some roles paying per project or task rather than hourly.

What does a typical day look like for a Data Labeler and how do team interactions work?

As a Data Labeler, your day typically involves reviewing, categorizing, and annotating large volumes of data such as images, text, or audio according to set guidelines. You’ll often work independently but may participate in regular team check-ins to discuss project updates, clarify instructions, or resolve ambiguous cases. Collaboration with data scientists or project managers is common when feedback or clarification is needed, ensuring consistency and quality across the labeled dataset. Over time, high-performing data labelers may transition into roles such as quality assurance reviewer or team lead. The work is detail-oriented and repetitive but is essential in powering reliable artificial intelligence and machine learning applications.

How much does Tesla pay data labelers?

Tesla data labelers typically earn between $15 and $25 per hour, depending on experience and location. The role involves annotating data for autonomous vehicle training and may require familiarity with labeling tools and attention to detail.

How to become a data labeler?

To become a data labeler, you typically need a high school diploma or equivalent and basic computer skills. Training is often provided by employers, and familiarity with data annotation tools or software can be helpful. Strong attention to detail and the ability to follow instructions are important for success in this role.

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

To thrive as a Data Labeler, you need strong attention to detail, proficiency in data entry, and a basic understanding of computer operations, often supported by a high school diploma or equivalent. Experience with annotation platforms, labeling tools, or specific data management software is valuable and may be required for some roles. Effective time management, patience, and the ability to follow detailed instructions are standout soft skills in this position. These skills ensure the accurate and efficient preparation of high-quality datasets, which are crucial for training reliable machine learning models.

What are popular job titles related to Data Labeler jobs in Spring, TX? For Data Labeler jobs in Spring, TX, the most frequently searched job titles are:
What job categories do people searching Data Labeler jobs in Spring, TX look for? The top searched job categories for Data Labeler jobs in Spring, TX are:
What cities near Spring, TX are hiring for Data Labeler jobs? Cities near Spring, TX with the most Data Labeler job openings:
Data Labeler jobs near you

Data Annotation Specialist

Bot Auto

Houston, TX • On-site

Full-time

Re-posted 20 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.

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