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Intern Data Annotation Tech Jobs in Houston, TX (NOW HIRING)

Bot Auto

Data Annotation Specialist

Houston, TX

Role Overview We are seeking a highly meticulous and motivated Data Annotation Specialist to join ... We are a small, hyper-focused team on a mission to beat human cost-per-mile through technology. We ...

Bot Auto

Data Annotation Specialist

Houston, TX · On-site

Role Overview We are seeking a highly meticulous and motivated Data Annotation Specialist to join ... We are a small, hyper-focused team on a mission to beat human cost-per-mile through technology. We ...

Baylor College of Medicine

Intern/Aide

Houston, TX · On-site

$10.62 - $14.44/hr

Intern/Aide Division: Urology Work Arrangement: Location: Houston, TX Salary Range: $10.62 - $14.44 ... Applies introductory scientific data analysis and image annotation techniques. * Learns to organize ...

Baylor College of Medicine

Intern/Aide

Houston, TX

$14.25 - $18.50/hr

Summary The intern/aide will learn core concepts of imaging cytometry and male infertility ... Applies introductory scientific data analysis and image annotation techniques. * Learns to organize ...

Mahindra Tractors

IT INTERN

Houston, TX · On-site

$12.50 - $16.50/hr

The IT intern will develop and utilize their critical thinking and project management skills to support software, hardware, programming, analytics, and data centre management. The IT intern will have ...

MetOx International, Inc.

Accounting Intern

Houston, TX · On-site

$15.25 - $19.25/hr

... technology. As an Accounting Intern, you'll join a dynamic team committed to strengthening the ... Assists with month-end close activities, including data gathering and reconciliation support.

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All JobsIntern Data Annotation Tech JobsIntern Data Annotation Tech Jobs in Houston, TX

Intern Data Annotation Tech information

Is data annotation real or fake?

Data annotation is a real and essential process in machine learning where human annotators label data such as images, text, or audio to train AI models. Interns in data annotation roles perform tasks like tagging and categorizing data using specialized tools, contributing to the development of accurate AI systems.

What are some common challenges faced by Intern Data Annotation Techs, and how can they overcome them?

Intern Data Annotation Techs often encounter challenges such as maintaining consistency in labeling large datasets and understanding nuanced instructions for annotation tasks. To overcome these hurdles, it's important to ask clarifying questions early on, regularly review annotation guidelines, and participate in team discussions about edge cases. Collaboration with more experienced annotators and feedback from supervisors also help in refining skills and ensuring high-quality data preparation. Developing attention to detail and adaptability will contribute to a successful internship experience.

Does data annotation tech really pay?

Data annotation technicians typically earn hourly wages that vary by experience and location, with entry-level positions often paying minimum wage or slightly above. The pay can increase with skill development, familiarity with annotation tools, and the complexity of the data being labeled. Overall, data annotation jobs provide a modest income but are generally not high-paying roles.

What is the difference between Intern Data Annotation Tech vs Intern Data Labeler?

AspectIntern Data Annotation TechIntern Data Labeler
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentData annotation platforms, remote or officeData labeling platforms, remote or office
Industry UsageAI, machine learning, data scienceAI, machine learning, data science
Job FocusAnnotating data for training AI modelsLabeling data for machine learning algorithms

Both roles involve preparing data for AI systems, with similar skills and work environments. The main difference lies in terminology; 'Data Annotation Tech' emphasizes technical annotation tasks, while 'Data Labeler' is a more general term. Both are entry-level positions vital for training AI models in the tech industry.

What is a data annotation intern?

A data annotation intern is a temporary position where individuals label or categorize data, such as images, text, or videos, to help train machine learning models. The role typically involves using annotation tools and requires attention to detail to ensure data accuracy, often under supervision or with specific guidelines.

Is data annotation tech still hiring?

Data annotation technician roles are currently in demand as companies expand AI and machine learning projects. These positions often require attention to detail and familiarity with annotation tools, and they are available in various industries including tech, healthcare, and automotive. Hiring trends indicate steady opportunities for entry-level and remote data annotation jobs.

What are Intern Data Annotation Techs?

Intern Data Annotation Techs are entry-level professionals, often students or recent graduates, who support machine learning projects by labeling and categorizing data, such as images, text, or audio. Their work is essential for training AI systems, as accurately annotated data helps algorithms learn to make correct predictions. These interns typically use specialized software tools to tag or classify data according to specific guidelines. The role requires attention to detail, consistency, and sometimes basic technical skills, depending on the complexity of the data and tasks. Internships in data annotation can provide valuable exposure to the fields of artificial intelligence and data science.

What are the key skills and qualifications needed to thrive as an Intern Data Annotation Tech, and why are they important?

To thrive as an Intern Data Annotation Tech, you need attention to detail, basic data management skills, and familiarity with data labeling concepts, often supported by a high school diploma or ongoing college coursework. Experience with annotation platforms, spreadsheet tools, and sometimes basic scripting languages is helpful. Strong communication, reliability, and the ability to follow detailed instructions are valuable soft skills in this role. These abilities ensure accurate and efficient data labeling, which is critical for training reliable machine learning models.
What are the most commonly searched types of Data Annotation Tech jobs in Houston, TX? The most popular types of Data Annotation Tech jobs in Houston, TX are:
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Intern Data Annotation Tech jobs near you

Data Annotation Specialist

Bot Auto

Houston, TX

Other

Posted 24 days ago

Job description

Company Introduction

At Bot Auto, we are revolutionizing the transportation of goods with our cutting-edge autonomous trucks, enhancing the quality of life for communities around the globe. With the agility of a startup and the wisdom of seasoned experts, our team has achieved numerous world-firsts and unparalleled innovations. United by a shared vision, we create groundbreaking solutions that propel the future of transportation. Join us and transform your ideas into reality.

Role Overview

We are seeking a highly meticulous and motivated Data Annotation Specialist to join our team. High-quality data is the lifeblood of our "Physical AI" and the foundation of our autonomous driving system. In this role, you will be responsible for creating, refining, and validating the ground-truth data that powers our perception and mapping stacks. You will work directly with our engineering teams to ensure our models are trained on high-fidelity, ground-truth data that meets our rigorous safety standards.

Key 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.
Required Qualifications
  • 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 Qualifications
  • 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.
Additional Information
  • Onsite Requirement: This position requires being onsite at our Houston, TX 5 days per week.
  • Benefits: Comprehensive benefits with the opportunity to work at the forefront of the autonomous trucking industry.
Why Bot Auto?

We are a small, hyper-focused team on a mission to beat human cost-per-mile through technology. We recently successfully completed the industry's first fully humanless commercial truckload, proving that our vision is a reality. If you are passionate about AI, safety, and transforming logistics, we want to hear from you.

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