ZipRecruiter

Log In

1

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

CirrusLabs

AI Data Engineer

Spring, TX · On-site

$101K - $122K/yr

They are seeking an AI Data Engineer with expertise in data structures and AI/ML workflows, responsible for designing data pipelines, integrating AI analytics, and collaborating with data modelers to ...

United Airlines

AI /ML Data Scientist

Houston, TX

$53K - $122K/yr

... driven AI/ML Engineer / GenAI Engineer / Data Scientist to join our dynamic Energy & Utilities ... This role is designed for emerging talent passionate about leveraging Artificial Intelligence to ...

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 ...

YO AI Labs

Graphic Designer Expert - Remote

Houston, TX · Remote

$20 - $50/hr

... annotation project. You'll use your expertise in typography, composition, visual hierarchy, and design systems to analyze and structure real-world creative assets for AI training. Scope of Work

previous pagenext page

Showing results 21-40

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

Data Annotation For Ai information

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 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 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 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 job categories do people searching Data Annotation For Ai jobs in Spring, TX look for?

The top searched job categories for Data Annotation For Ai jobs in Spring, TX are:

What cities near Spring, TX are hiring for Data Annotation For Ai jobs?

Cities near Spring, TX with the most Data Annotation For Ai job openings:

Data Annotation For Ai jobs near you

AI Data Engineer

Spring, TX • On-site

CirrusLabs
IT Services • 11 - 50 employees
Learn more about CirrusLabsexternal

$101K - $122K/yr

Full-time

Re-posted 18 days ago

Job description

Job Summary:
CirrusLabs is a niche digital transformation company dedicated to helping customers realize value through innovation. They are seeking an AI Data Engineer with expertise in data structures and AI/ML workflows, responsible for designing data pipelines, integrating AI analytics, and collaborating with data modelers to optimize datasets for AI model training.
Responsibilities:
• 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 model monitoring.
• Integrate AI-powered analytics and predictive models into business intelligence tools like Power BI.
• Evaluate and implement AI services (e.g., Azure Cognitive Services, OpenAI, or custom ML models) to enhance data products and user experiences.
Qualifications:
Required:
• SQL, DBT, ADF, DAX, Power BI, Snowflake
• AI/ML Integration: Experience integrating AI/ML models into data pipelines and analytics platforms.
• Data Modeling: Hands-on experience in designing and implementing complex data models, with a strong understanding of normalization, denormalization, and schema designs such as star schema and snowflake schema.
• Ingestion Processes: Hands-on experience in developing and optimizing EL (Extract and Load) processes using ADF (Azure Data Factory).
• Data Transformation Processes: Hands-on experience in developing and optimizing DBT (Data Build Tool) models, including data testing.
• Data Warehousing: Understanding of data warehousing concepts and best practices, particularly with the Snowflake platform, including optimization strategies, query tuning, and clustering.
• Cloud Platforms: Experience with Azure, particularly in relation to data storage, integration, processing, and AI services.
• Programming Languages: Proficiency in SQL and DAX; familiarity with Python or R for AI/ML tasks is a plus.
• Visualization Expertise: Experience creating interactive and performant visualizations using Power BI, including designing and maintaining semantic models.
• AI Training & Development: Experience working with the data, systems, and architecture to train and develop new AI-powered analytics and functionality.
Preferred:
• Microsoft Certified: Azure AI Engineer Associate (Optional but valuable)
• AI-102: Designing and Implementing an Azure AI Solution (Recommended)
Company:
CirrusLabs is an IT company provides agile software delivery, automation, cloud Services, and IoT. Founded in 2005, the company is headquartered in Alpharetta, USA, with a team of 201-500 employees. The company is currently Growth Stage.

Apply