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Data Annotation Manager Jobs in Austin, TX (NOW HIRING)

Description You will lead an organization of internal domain experts, building scalable annotation ... Prior experience managing a data operations team. Minimum Qualifications MS in Computer Science ...

WHAT YOU'LL DO • Execute Data labelling and annotation tasks across speech and voice datasets. • Work with audio and language data, including transcription, categorization, and tagging. YOU ARE A ...

WHAT YOU'LL DO • Execute Data labelling and annotation tasks across speech and voice datasets. • Work with audio and language data, including transcription, categorization, and tagging. YOU ARE A ...

Platform Engineer, Data

Austin, TX

$113K - $136K/yr

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 ...

Platform Engineer, Data

Austin, TX · On-site

$113K - $136K/yr

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 ...

Platform Engineer, Data

Austin, TX · On-site

$113K - $136K/yr

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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Data Annotation Manager information

See Austin, TX salary details

$30.7K

$96.3K

$170.5K

How much do data annotation manager jobs pay per year?

As of Jun 13, 2026, the average yearly pay for data annotation manager in Austin, TX is $96,291.00, according to ZipRecruiter salary data. Most workers in this role earn between $65,400.00 and $124,400.00 per year, depending on experience, location, and employer.

What is the salary of data annotation manager?

The salary of a Data Annotation Manager typically ranges from $60,000 to $120,000 annually, depending on experience, location, and company size. Senior roles or those in high-cost areas may offer higher compensation, and proficiency with annotation tools and team management can influence pay levels.

Is data annotation high paying?

Data annotation managers typically earn higher salaries than entry-level annotators due to their supervisory responsibilities and expertise in labeling tools and processes. Salaries vary based on experience, location, and company size, but the role generally offers competitive pay within the data labeling industry.

Is data annotation real or fake?

Data annotation is a real and essential process in machine learning and AI development, involving labeling data such as images, text, or audio to train algorithms. Data annotation managers oversee this work, ensuring accuracy and quality using tools like labeling platforms and quality control procedures.

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 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.

Is it hard to get a job with data annotation?

Securing a job as a data annotation manager typically requires experience in data labeling, familiarity with annotation tools, and understanding of data quality standards. While entry-level roles may be accessible with basic skills, advancing to managerial positions often demands relevant experience and leadership abilities.

What are the key skills and qualifications needed to thrive as a Data Annotation Manager, and why are they important?

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 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 Austin, TX? The most popular types of Data Annotation jobs in Austin, TX are:
What are popular job titles related to Data Annotation Manager jobs in Austin, TX? For Data Annotation Manager jobs in Austin, TX, the most frequently searched job titles are:
What job categories do people searching Data Annotation Manager jobs in Austin, TX look for? The top searched job categories for Data Annotation Manager jobs in Austin, TX are:
What cities near Austin, TX are hiring for Data Annotation Manager jobs? Cities near Austin, TX with the most Data Annotation Manager job openings:
Infographic showing various Data Annotation Manager job openings in Austin, TX as of June 2026, with employment types broken down into 100% Full Time. Highlights an 74% In-person, and 26% Remote job distribution, with an average salary of $96,291 per year, or $46.3 per hour.

Data Annotation Specialist

Saronic Technologies

Austin, TX • On-site

Contractor

Posted 23 days ago


Job description

Saronic Technologies is a leader in revolutionizing autonomy at sea, dedicated to developing state-of-the-art solutions that enhance maritime operations through autonomous and intelligent platforms.
Job Overview
We are seeking a Data Annotation Specialist to annotate and review visual datasets used to train and evaluate machine-learning models for maritime perception and autonomy. This role supports our software, perception, and autonomy teams by ensuring labeled data is accurate, consistent, and useful for model development.
The ideal candidate has prior computer vision annotation experience, strong visual attention to detail, and the ability to maintain speed and accuracy through repetitive labeling work. This person should be comfortable following detailed instructions, adapting as labeling rules change, and supporting a fast-moving technical team.
This is an on-site, full-time contract role with an intended path to full-time conversion based on performance and business needs. Upon conversion, the employee would be eligible for Saronic's standard full-time benefits. This position reports to the Data Annotation Manager.
Responsibilities
  • Annotate and review large volumes of image, video, infrared, and other sensor data using computer vision labeling methods.
  • Identify vessels, objects, environmental features, and other elements relevant to maritime autonomy.
  • Maintain accuracy, consistency, and productivity across repetitive, detail-heavy datasets.
  • Apply evolving labeling guidelines and escalate unclear edge cases when needed.
  • Perform both manual annotation work and quality review of auto-labeled data as needed.
  • Willingness to support priority project deadlines when needed.
Qualifications
  • Prior experience in computer vision data annotation or labeling.
  • Familiarity with annotation tools such as Labelbox, CVAT, or similar
  • Experience with annotation types such as segmentation masks, bounding boxes, key points, object tracking, or classification.
  • Strong visual pattern recognition, spatial reasoning, and attention to detail.
  • Comfortable performing repetitive, process-driven work for extended periods while maintaining quality.
  • Able to adapt to changing project priorities, labeling rules, and quality standards in a fast-paced environment.
  • Strong communication skills and willingness to ask questions, accept feedback, and collaborate with the team.
  • Basic understanding of maritime environments, autonomous systems, robotics, or defense technology is a plus.

Saronic CCPA Notice for Candidates and California Employees
If this role is based in the United States, it requires access to export-controlled information or items that require "U.S. Person" status. As defined by U.S. law, individuals who are any one of the following are considered to be a "U.S. Person": (1) U.S. citizens, (2) legal permanent residents (a.k.a. green card holders), and (3) certain protected classes of asylees and refugees, as defined in 8 U.S.C. 1324b(a)(3).
Saronic does not discriminate on the basis of race, sex, color, religion, age, national origin, marital status, disability, veteran status, genetic information, sexual orientation, gender identity or any other reason prohibited by law in provision of employment opportunities and benefits.