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Vision Labeling Jobs in Texas (NOW HIRING)

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Flexo Press Operator (1st Shift or 2nd Shift availabilities)

Dallas, TX · On-site

$21.25 - $28.25/hr

... labels and related products. Hours : Monday - Thursday, 10 hour day shift (Overtime as needed ... Specific vision abilities required by this job include close vision, color vision, depth perception ...

Avery Dennison

Label Machine Operator - A Shift

Dallas, TX · On-site

$15.50 - $18.50/hr

We design and develop labeling and functional materials, radio-frequency identification (RFID ... Color vision proficiency to distinguish product variations. Additional Information Additional ...

Avery Dennison

Label Machine Operator - A Shift

Dallas, TX · On-site

$15.50 - $18.50/hr

We design and develop labeling and functional materials, radio-frequency identification (RFID ... Color vision proficiency to distinguish product variations. Additional Information Additional ...

Waabi

Senior Software Engineer, Auto Labelling

Dallas, TX · On-site +1

$170K - $220K/yr

... vision, and machine learning. - Manage the end-to-end orchestration of the large-scale auto-labelling training, evaluation and automation eco-system. - Architect and scale the pipeline to handle ...

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Vision Labeling information

What is vision labeling?

Vision labeling is the process of manually or automatically tagging objects, features, or attributes within images or videos. This data is essential for training computer vision models, which are used in applications like facial recognition, autonomous vehicles, and medical imaging. Vision labeling tasks can include identifying objects, outlining shapes, or classifying scenes. Accurate labeling helps improve the performance and reliability of artificial intelligence systems that rely on visual data.

What is the difference between Vision Labeling vs Data Annotation?

AspectVision LabelingData Annotation
CredentialsTypically requires basic technical skills, familiarity with labeling toolsSimilar, often requires understanding of annotation standards
Work EnvironmentData labeling platforms, remote or on-siteSame as Vision Labeling, often overlapping tools
Industry UsageUsed in AI training for computer vision tasksUsed across AI fields, including NLP and vision
Search & ComparisonFocused on visual data, images, videosBroader, includes text, audio, and visual data

Vision Labeling and Data Annotation are closely related roles in AI data preparation. Vision Labeling specifically involves tagging and categorizing visual data like images and videos, while Data Annotation encompasses a wider range of data types, including text and audio. Both roles require similar skills and tools, but Vision Labeling is specialized for computer vision projects.

What are the main challenges faced by vision labeling specialists, and how can they overcome them?

Vision labeling specialists often encounter challenges such as maintaining high accuracy when annotating complex images, managing repetitive tasks, and meeting tight project deadlines. To overcome these issues, it helps to stay updated on best practices, use quality control tools provided by the employer, and actively participate in team discussions to clarify ambiguous cases. Collaborating closely with machine learning engineers and team leads also ensures labels meet project requirements and helps address any uncertainties quickly.

What are the key skills and qualifications needed to thrive as a Vision Labeling Specialist, and why are they important?

To thrive as a Vision Labeling Specialist, you need strong attention to detail, basic computer literacy, and familiarity with image annotation concepts, often supported by a high school diploma or relevant experience. Proficiency with labeling platforms such as Labelbox, Supervisely, or CVAT, as well as understanding data annotation guidelines, is typically required. Patience, consistency, and effective communication help individuals excel in repetitive tasks and collaborate with quality assurance teams. These skills and qualities are vital to ensure the accuracy and reliability of labeled datasets used to train computer vision models.
What are popular job titles related to Vision Labeling jobs in Texas? For Vision Labeling jobs in Texas, the most frequently searched job titles are:
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What cities in Texas are hiring for Vision Labeling jobs? Cities in Texas with the most Vision Labeling job openings:
Vision Labeling jobs near you
Junior/Middle Computer Vision Engineer ID72410

Junior/Middle Computer Vision Engineer ID72410

AgileEngine

Dallas, TX • On-site

Full-time

This job post has expired today. Applications are no longer accepted.

Job description


AgileEngine is an Inc. 5000 company that creates award-winning software for Fortune 500 brands and trailblazing startups across 17+ industries. We rank among the leaders in areas like application development and AI/ML, and our people-first culture has earned us multiple Best Place to Work awards.
WHY JOIN US
If you're looking for a place to grow, make an impact, and work with people who care, we'd love to meet you!
ABOUT THE ROLE
We are looking for a Junior/Middle Computer Vision Engineer to support high-volume execution across data preparation, model training, and evaluation for an AI team working with large-scale image and video datasets. You will curate and manage annotation workflows, run model training and evaluation jobs, maintain benchmarks, and collaborate with senior engineers on failure-case analysis. The role offers a clear growth path into applied modeling or MLOps for an early-career engineer eager to build hands-on AI experience.
WHAT YOU WILL DO
- Curate large-scale image and video datasets, manage labeling processes and workflows, and ensure the highest standards for dataset quality;
- Run model training and evaluation jobs, ensuring experiments are executed smoothly and efficiently;
- Document training results, maintain ongoing evaluation benchmarks, and track model performance over time;
- Collaborate with senior engineers to analyze model failure cases and identify areas for data or algorithmic improvement;
- Take ownership of foundational tasks that support the broader team's AI/ML lifecycle, directly contributing to the speed and success of production deployments.
MUST HAVES
- You must be authorized to work for ANY employer in the US (e.g., Green card holders, TN visa holders, GC EAD, H4 EAD, U4U with EAD), as we are unable to sponsor or take over employment visa sponsorship at this time;
- 1 to 3 years of experience in software engineering, data science, machine learning, or a related field;
- Degree in Computer Science, Data Science, Engineering, Mathematics, or a related discipline (or equivalent practical experience);
- Engineers located in the US must reside in Dallas, TX, and be open to working from the office (onsite);
- Foundational coding skills in Python;
- Foundational understanding of machine learning concepts and workflows;
- Basic knowledge of computer vision principles (e.g., image processing, object detection basics);
- Basic familiarity with cloud environments and compute resources;
- A strong, demonstrable willingness to learn and adapt in a fast-paced, mentorship-driven environment;
- Excellent attention to detail, specifically regarding data quality and documentation;
- Upper-intermediate English level.
PERKS AND BENEFITS
- Professional growth: Mentorship, TechTalks, and personalized growth roadmaps.
- Competitive compensation: USD-based pay with education, fitness, and team activity budgets.
- Exciting projects: Modern solutions with Fortune 500 and top product companies.
- Flextime: Flexible schedule with remote and office options.
Meet Our Recruitment Process
Application → Coding Challenge → Video Interview → Technical Interview or Hiring Manager Interview
Each step helps us understand your skills and overall fit.
If it's a match, you'll receive an offer.

Apply