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Data Annotation Manager Jobs in Texas (NOW HIRING)

Allen Control Systems

Platform Engineer, Data

Austin, TX · On-site

$113K - $136K/yr

... drift, and annotation error; active-learning sampling to target gaps; feedback loops from ... management, and lineage and metadata cataloging. Qualifications : Required : • 3+ years of ...

Allen Control Systems

Platform Engineer, Data

Austin, TX · On-site

$113K - $136K/yr

... drift, and annotation error; active-learning sampling to target gaps; feedback loops from ... management, and lineage and metadata cataloging. Qualifications : Required : • 3+ years of ...

Allen Control Systems

Platform Engineer, Data

Austin, TX · On-site

$113K - $136K/yr

... drift, and annotation error; active-learning sampling to target gaps; feedback loops from ... management, and lineage and metadata cataloging. Qualifications : Required : • 3+ years of ...

Allen Control Systems

Platform Engineer, Data

Austin, TX · On-site

$113K - $136K/yr

... drift, and annotation error; active-learning sampling to target gaps; feedback loops from ... management, and lineage and metadata cataloging. Qualifications : Required : • 3+ years of ...

Allen Control Systems

Platform Engineer, Data

Austin, TX · On-site

$113K - $136K/yr

  • Medical

  • Dental

  • Vision

  • PTO

Develop and use data quality tooling: metrics for balance, drift, and annotation error; active ... Implement and own dataset versioning, release management, and lineage and metadata cataloging. What ...

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Showing results 21-40

All JobsData Annotation JobsData Annotation Manager JobsData Annotation Manager Jobs in Texas

Data Annotation Manager information

See Texas salary details

$28.9K

$90.5K

$160.2K

How much do data annotation manager jobs pay per year?

As of Aug 18, 2026, the average yearly pay for data annotation manager in Texas is $90,505.00, according to ZipRecruiter salary data. Most workers in this role earn between $61,500.00 and $116,900.00 per year, depending on experience, location, and employer.

What does a data annotation manager do?

A Data Annotation Manager oversees the process of labeling and categorizing data used to train machine learning models. They manage teams of annotators, ensure data quality, develop annotation guidelines, and coordinate with data scientists to meet project requirements. Their role is critical in maintaining high standards of accuracy and efficiency, as well as ensuring that datasets are properly prepared for AI and machine learning applications.

What are the key skills and qualifications needed to thrive as a data annotation manager?

To thrive as a Data Annotation Manager, you need expertise in data labeling processes, quality control, and a solid understanding of machine learning concepts, usually backed by a degree in computer science or a related field. Proficiency with annotation tools such as Labelbox, Supervisely, or CVAT, as well as experience with project management systems, is commonly required. Exceptional leadership, attention to detail, and strong communication skills help manage teams and ensure high annotation accuracy. These skills are critical for delivering reliable labeled datasets, which are essential for building effective AI and machine learning models.

What are some common challenges faced by data annotation managers, and how can they be addressed?

Data Annotation Managers often encounter challenges such as maintaining high annotation quality across large and diverse datasets, managing a distributed team of annotators, and meeting tight project deadlines. To address these, it's important to implement robust quality assurance processes, provide ongoing training for annotators, and establish clear communication channels. Leveraging annotation tools with built-in validation features can also help ensure consistency and accuracy. Building a positive and collaborative team environment further contributes to better outcomes and workflow efficiency.

What is the difference between Data Annotation Manager vs Data Labeling Specialist?

AspectData Annotation ManagerData Labeling Specialist
CredentialsBachelor's degree in related field, experience in data managementHigh school diploma or equivalent, training in labeling tools
Work EnvironmentTeam management, project oversight, collaboration with data scientistsHands-on labeling work, using annotation tools, focused on data tagging
Industry UsageUsed in AI/ML projects for overseeing annotation teamsPerforms the actual data labeling tasks in machine learning workflows

The Data Annotation Manager oversees the entire annotation process, managing teams and ensuring quality, while the Data Labeling Specialist focuses on executing labeling tasks. Both roles are essential in AI/ML data preparation but differ in responsibilities and scope.

What are the most commonly searched types of Data Annotation jobs in Texas?

The most popular types of Data Annotation jobs in Texas are:

What are popular job titles related to Data Annotation Manager jobs in Texas?

For Data Annotation Manager jobs in Texas, the most frequently searched job titles are:

What job categories do people searching Data Annotation Manager jobs in Texas look for?

The top searched job categories for Data Annotation Manager jobs in Texas are:

What cities in Texas are hiring for Data Annotation Manager jobs?

Cities in Texas with the most Data Annotation Manager job openings:

Data Annotation Manager jobs near you
Infographic showing various Data Annotation Manager job openings in Texas as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $90,505 per year, or $43.5 per hour.

Platform Engineer, Data

Allen Control Systems

Austin, TX • On-site

$113K - $136K/yr

Full-time

Re-posted 3 days ago

Job description

Job Summary:
Allen Control Systems (ACS) is a cutting-edge defense startup focused on developing innovative technologies for autonomous targeting systems. They are seeking a Data Platform Engineer with expertise in data infrastructure and AI & Machine Learning principles to design and implement data optimization strategies for model training and maintain large-scale data pipelines.
Responsibilities:
• Design and develop a scalable data infastructure, focusing on organization and curation to support continuing increases in data volume and complexity
• Design and implement existing and novel approaches to optimize datasets for model training (e.g., hard example mining, class balancing, de-duplication, embedded-based filtering).
• Support the data infrastructure required for optimal ingestion, transformation, and storing of datasets
• Develop and use synthetic data generation workflows to create realistic synthetic training data for computer vision models.
• Design and own end-to-end image and video pipelines for computer vision model training: multi-source ingestion, QA and visualization, standardization, and organization.
• Coordinate collection of real-world data; coordinate label creation and QA with labelers.
• Develop and use data quality tooling: metrics for balance, drift, and annotation error; active-learning sampling to target gaps; feedback loops from production back to curation.
• Implement and own dataset versioning, release management, and lineage and metadata cataloging.
Qualifications:
Required:
• 3+ years of experience in data engineering or equivalent fields.
• Solid understanding of data structures and systems design for orchestrating data-related workflows in a rapidly growing environment.
• Proficient in using AWS for data management and processing.
• Proficient in Python for scripting and data processing; proficient with SQL and Linux.
• Educational Background: Bachelor’s or Master’s degree in Computer Science or a related field.
• Proven ability to communicate well across engineering teams, and write and maintain effective documentation.
Preferred:
• 5+ years of industry experience.
• Experience in image/video data engineering for computer vision projects.
• Experience with PyTorch DeepCore.
• Experience with Unreal Engine.
Company:
Allen Control Systems develops autonomous defense technologies designed to detect, track, and counter unmanned aerial threats. Founded in 2022, the company is headquartered in Austin, USA, with a team of 201-500 employees. The company is currently Growth Stage.

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