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Data Annotation For Ai Jobs in Spring, TX (NOW HIRING)

Bot Auto

Data Annotation Specialist

Houston, TX · On-site

Preferred : • Prior experience in data annotation for autonomous driving, robotics, or computer vision. • Understanding of autonomous vehicle sensor modalities (LiDAR, Radar, Cameras). • ...

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

... 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 ...

CirrusLabs

AI Data Engineer

Spring, TX · On-site

$96K - $116K/yr

Collaborate with data modelers to prepare and optimize datasets for AI model training and inference ... Design and implement data pipelines that support AI/ML workflows, including feature engineering and ...

Deloitte

Agentic AI, AI & Data Consultant

Houston, TX · On-site

... software, data, AI, network, and hybrid cloud infrastructure. These solutions are powered by ... Recruiting for this role ends on 6/6/2026 Work you'll do You will leverage your deep subject matter ...

NAVA Software Solutions

Data/AI Lead

Houston, TX · On-site

NAVA Software solutions is looking for a Data/AI Lead Details: Data/AI Lead Location: Houston TX - 3 days /week Duration: Direct Hire / Full time role SUMMARY OF THE ROLE Responsible for leading the ...

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All JobsData Annotation For Ai JobsData Annotation For Ai Jobs in Spring, TX

Data Annotation For Ai information

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.

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.

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.

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 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.
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Data Annotation For Ai jobs near you

Data Annotation Specialist

Bot Auto

Houston, TX • On-site

Full-time

Posted 17 days ago

Job description

Job Summary:
Bot Auto is revolutionizing the transportation of goods with cutting-edge autonomous trucks. They are seeking a highly meticulous and motivated Data Annotation Specialist to create, refine, and validate the ground-truth data that powers their 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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