1

Data Annotation Engineer Jobs in Texas (NOW HIRING)

Delivery Lead

Austin, TX · Remote

$110K - $140K/yr

... data creation to annotation to delivery. We design and create datasets from scratch, recruit and ... Partner with Product and Engineering to evolve internal tooling, automation, and operational ...

New

Delivery Lead

Dallas, TX · Remote

$110K - $140K/yr

... data creation to annotation to delivery. We design and create datasets from scratch, recruit and ... Partner with Product and Engineering to evolve internal tooling, automation, and operational ...

New

next page

Showing results 1-20

Data Annotation Engineer information

See Texas salary details

$48K

$137.4K

$183.5K

How much do data annotation engineer jobs pay per year?

As of May 30, 2026, the average yearly pay for data annotation engineer in Texas is $137,383.00, according to ZipRecruiter salary data. Most workers in this role earn between $78,300.00 and $182,600.00 per year, depending on experience, location, and employer.

What is a Data Annotation Engineer job?

A Data Annotation Engineer is responsible for labeling and annotating data—such as text, images, audio, or video—to train machine learning models. They ensure that data is accurately categorized and structured to improve model performance. This role often involves using specialized annotation tools, following detailed guidelines, and working closely with data scientists and AI teams. Data Annotation Engineers play a crucial role in the development of AI applications by providing high-quality labeled datasets for supervised learning.

What are the key skills and qualifications needed to thrive in the Data Annotation Engineer position, and why are they important?

To thrive as a Data Annotation Engineer, you need a strong background in data analysis, attention to detail, and familiarity with annotation processes, often supported by a degree in computer science or a related field. Proficiency with annotation tools like Labelbox, CVAT, or VIA, and understanding of data formats used in machine learning, is commonly required. Excellent communication, collaboration, and organizational skills help you effectively manage projects and cooperate with cross-functional teams. These abilities are crucial for delivering high-quality labeled data, which directly impacts the performance of AI and machine learning models.

What are the main challenges faced by Data Annotation Engineers in their daily work?

One of the main challenges Data Annotation Engineers face is ensuring consistent accuracy and quality in labeling large and often complex datasets. Attention to detail is critical, as even small errors can significantly affect machine learning model performance. Additionally, engineers must frequently adapt to evolving annotation guidelines and emerging data types, which requires ongoing learning and flexibility. Collaboration with data scientists and project managers is common to clarify requirements and resolve ambiguities, making strong communication skills essential for success.
What are popular job titles related to Data Annotation Engineer jobs in Texas? For Data Annotation Engineer jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Data Annotation Engineer jobs in Texas look for? The top searched job categories for Data Annotation Engineer jobs in Texas are:
What cities in Texas are hiring for Data Annotation Engineer jobs? Cities in Texas with the most Data Annotation Engineer job openings:
Infographic showing various Data Annotation Engineer job openings in Texas as of May 2026, with employment types broken down into 33% As Needed, and 67% Part Time. Highlights an 5% Physical, and 95% Remote job distribution, with an average salary of $137,383 per year, or $66 per hour.
Visual Data Labeling Technician I (Part-Time)

Visual Data Labeling Technician I (Part-Time)

AST SpaceMobile

Midland, TX

$20/hr

Part-time

Posted 15 days ago


Job description

AST SpaceMobile is building the first and only global cellular broadband network in space to operate directly with standard, unmodified mobile devices based on our extensive IP and patent portfolio and designed for both commercial and government applications. Our engineers and space scientists are on a mission to eliminate the connectivity gaps faced by today's five billion mobile subscribers and finally bring broadband to the billions who remain unconnected.

Role Summary

AST SpaceMobile is hiring part-time Visual Data Labeling Technician I in Midland, TX to label imagery of spacecraft components, sub-assemblies, and factory-floor assembly steps used to train AST's computer-vision and robotics AI models.

Working on-site in the AI Lab, you will use AST's in-house labeling software to draw bounding boxes, polygons, and segmentation masks; classify components and defects; and follow detailed labeling guidelines defined by AST's data scientists and manufacturing quality engineers. This is a high-precision, security-controlled role: the lab is a no-personal-electronics environment, and your accuracy and consistency directly determine the quality of the AI models AST relies on for visual inspection and robotic operation.

The role is well suited to detail-oriented people who enjoy focused screen work, take pride in careful documentation, and want to contribute to the next generation of space-based connectivity.

Key Responsibilities

  • Label images and short video clips of spacecraft components, sub-assemblies, and assembly steps using AST's in-house computer-vision labeling software
  • Apply bounding boxes, polygons, segmentation masks, keypoints, and classification tags according to AST's labeling guidelines and ontology
  • Maintain a high level of accuracy and consistency across labeling tasks, meeting throughput and quality targets set by the AI Lab Manager
  • Flag ambiguous, defective, or unusual images for review by quality inspectors, engineers, or data scientists
  • Participate in calibration sessions, inter-rater agreement reviews, and ontology refinement discussions
  • Follow all AI Lab security and operations rules, including no personal cell phones, cameras, personal electronics, or removable storage media in the lab
  • Maintain accurate logs of completed work batches, time on task, and any issues encountered
  • Partner with the AI Lab Manager and quality inspectors during on-floor image-capture sessions when required

Required Qualifications

  • High school diploma or equivalent
  • Strong attention to detail and ability to maintain accuracy on repetitive visual tasks for sustained periods
  • Basic computer literacy: comfortable using a mouse, keyboard, and web-based or desktop labeling tools
  • Ability to follow written instructions, ontologies, and quality guidelines closely
  • Ability to be physically on-site in Midland, TX for the agreed part-time schedule
  • Willingness to comply with strict no-personal-electronics, no-photography, and no-removable-media lab rules

Preferred Qualifications

  • Prior experience with image annotation, data labeling, or QA work
  • Familiarity with labeling tools such as CVAT, Labelbox, Scale, or similar platforms
  • Background in manufacturing quality, optical inspection, photography, or technical documentation
  • Interest in AI, computer vision, robotics, or aerospace
  • Coursework or certificate in computer technology, drafting, electronics, or related field

Compensation & Benefits

  • Base hourly rate of $20.00/ hour
  • Part-time, on-site role in Midland, TX
  • Opportunity to contribute directly to AI models that support spacecraft manufacturing and operations
  • We are flexible with work hours between 8am and 6pm, Monday through Friday. We are able to work around school schedules, daycare, and appointments. Great part time work!

This job description may not be inclusive to the duties and responsibilities listed. Additional tasks may be assigned to the employee from time to time or the scope of the job may change as needed by business demands.

AST SpaceMobile is an Equal Opportunity, at will Employer; employment is governed on the basis of merit, competence and qualifications and will not be influenced in any manner by race, color, religion, gender, national origin/ethnicity, veteran status, disability status, age, sexual orientation, gender identity, marital status, mental or physical disability or any other legally protected status.