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Data Annotation For Ai Jobs (NOW HIRING)

Bot Auto

Data Annotation Specialist

Houston, TX

... AI" and the foundation of our autonomous driving system. In this role, you will be responsible for ... Prior experience in data annotation for autonomous driving, robotics, or computer vision.

Bot Auto

Data Annotation Specialist

Houston, TX · On-site

... AI" and the foundation of our autonomous driving system. In this role, you will be responsible for ... Prior experience in data annotation for autonomous driving, robotics, or computer vision.

Bot Auto

Data Annotation Specialist

Houston, TX · On-site

They are seeking a meticulous Data Annotation Specialist responsible for creating, refining, and validating the ground-truth data for their autonomous driving system, ensuring high-quality data meets ...

Bot Auto

Data Annotation Specialist

Houston, TX · On-site

They are seeking a highly meticulous and motivated Data Annotation Specialist to create, refine, and validate the ground-truth data for their autonomous driving system, working closely with ...

Encord

Human Data Operations Strategist

San Francisco, CA · On-site

$150K - $230K/yr

Oversee data annotation projects, translating complex AI and machine learning requirements into clear workflows and instructions for data annotation teams * Ensure the highest standards of data ...

Gehc

Data Manager - AI Development

Waukesha, WI

This role works closely with AI/ML engineers to define data needs for AI features, coordinates with internal and external data collection teams/clinical team, oversees annotation activities, and ...

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Data Annotation For Ai information

What are the key skills and qualifications needed to thrive as a Data Annotation Specialist for AI, and why are they important?

To thrive as a Data Annotation Specialist for AI, you need a keen eye for detail, a solid understanding of data labeling concepts, and often a background in the relevant domain (such as language, images, or audio). Proficiency with annotation platforms, data management systems, and basic familiarity with tools like Excel or Python can be highly valuable. Strong communication, consistency, and time management skills help ensure accuracy and meet project deadlines. These abilities are crucial because high-quality, well-annotated data is foundational for training reliable and effective AI models.

What are some common challenges faced by data annotators working on AI projects, and how can they be addressed?

Data annotators for AI often encounter challenges such as maintaining consistency across large datasets, understanding ambiguous labeling instructions, and managing repetitive tasks. To address these issues, it's important to actively seek clarification on guidelines, participate in team discussions to align on labeling standards, and use annotation tools that flag inconsistencies. Regular feedback sessions with project leads also help improve accuracy and efficiency, fostering a collaborative and supportive work environment.

What is data annotation for AI?

Data annotation for AI is the process of labeling or tagging data—such as text, images, audio, or video—to make it understandable for machine learning models. Annotators add relevant information to raw data, helping AI systems learn to recognize patterns and make accurate predictions. This step is crucial for training, validating, and testing AI algorithms, especially in tasks like computer vision and natural language processing. High-quality data annotation directly impacts the effectiveness and reliability of AI applications.

How to become an AI data annotator?

To become an AI data annotator, you typically need strong attention to detail, good communication skills, and familiarity with annotation tools or platforms. Many roles require a high school diploma or equivalent, and some may prefer experience with specific data types like images, text, or audio. Training is often provided by employers, and the work can be part-time or flexible, depending on the company.

What is the difference between Data Annotation For Ai vs Data Labeler?

AspectData Annotation For AiData Labeler
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentRemote or on-site, tech companies, AI projectsRemote or on-site, data processing companies
Industry UsageArtificial Intelligence, Machine LearningData management, content moderation
Job FocusPreparing data for AI algorithms through annotationLabeling data for various purposes, including AI

Data Annotation For Ai involves preparing datasets specifically for training AI models, focusing on detailed annotations. Data Labeler is a broader role that includes labeling data for multiple purposes, including AI but also other data management tasks. While both roles require similar skills, Data Annotation For Ai is more specialized towards AI development projects.

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Infographic showing various Data Annotation For Ai job openings in the United States as of May 2026, with employment types broken down into 91% Full Time, 3% Part Time, and 6% Contract. Highlights an 91% Physical, 7% Hybrid, and 2% Remote job distribution.

Data Annotation Specialist

Bot Auto

Houston, TX

Other

Posted 7 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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