1

Data Annotation Manager Jobs in Kentucky (NOW HIRING)

Performs data entry operations using appropriate hospital software package. Staff member may be ... Utilizes RIS, PACS and other, ancillary image management systems as needed. Maintains equipment in ...

Performs data entry operations using appropriate hospital software package. Staff member may be ... Utilizes RIS, PACS and other, ancillary image management systems as needed * assists in ...

Performs data entry operations using appropriate hospital software package. Staff member may be ... Utilizes RIS, PACS and other, ancillary image management systems as needed. * Plans, schedules, and ...

Data Annotation Manager information

See Kentucky salary details

$26.9K

$84.4K

$149.4K

How much do data annotation manager jobs pay per year?

As of Aug 2, 2026, the average yearly pay for data annotation manager in Kentucky is $84,373.00, according to ZipRecruiter salary data. Most workers in this role earn between $57,300.00 and $109,000.00 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 familiarity with annotation tools and team management can influence pay levels.

How much do data annotation project managers make?

Data annotation project managers typically earn between $60,000 and $100,000 annually, depending on experience, location, and company size. They oversee annotation teams, coordinate workflows, and ensure quality standards are met, often requiring familiarity with annotation tools and project management skills.

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.

Does data annotation actually pay well?

Data annotation managers typically earn competitive salaries that reflect their experience and responsibilities, often ranging from entry-level to senior roles. Compensation can vary based on industry, location, and company size, with specialized skills in tools like labeling platforms and quality control often leading to higher pay.

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.

How hard is it to get hired by data annotation?

Getting hired as a data annotation manager typically requires relevant experience in data labeling, familiarity with annotation tools, and strong organizational skills. The hiring process often involves reviewing previous work, technical assessments, and demonstrating attention to detail, with opportunities available in companies that outsource data labeling tasks.

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 Kentucky? The most popular types of Data Annotation jobs in Kentucky are:
What are popular job titles related to Data Annotation Manager jobs in Kentucky? For Data Annotation Manager jobs in Kentucky, the most frequently searched job titles are:
What cities in Kentucky are hiring for Data Annotation Manager jobs? Cities in Kentucky with the most Data Annotation Manager job openings:

Data Annotation reviewer (QA) (GenAI/LLM)

Pro Integrate

Louisville, KY โ€ข On-site

Other

Posted 17 days ago


Job description

Data Annotation reviewer (QA) (GenAI/LLM) role - Onsite -

Location: Louisville, KY

Duration: 2+ months with possibility if extensions

Role Description

As QA at Centific specializing in Generative AI Data Services, you will play a pivotal role in driving the success of our cutting-edge projects focused on building and enhancing Large Language Models (LLMs). Your primary responsibility will be to adhere to quality review instructions, pass, review or reject human-labeled data crucial for training AI models. In this dynamic and evolving field, you will be at the forefront of bridging the gap between human expertise and artificial intelligence, contributing significantly to the development of next-generation AI technologies. As a problem solver and highly organized lead, you will collaborate closely with internal teams and a global workforce, ensuring seamless communication, efficient execution, and successful delivery of projects.

Task Overview:
As a Data Annotation Reviewer, you will evaluate data annotation and bounding box responses from annotators. Your job is to ensure the correct annotation was applied within the input parameters match and the output is accurate and relevant according to the guidelines.

Key Responsibilities:

  • Review annotations to confirm they match the intended purpose of the guidelines.
  • Validate that the annotator answer is appropriate for the chosen function.
  • Check if the Annotation output includes all necessary information to filfull the guidelines.
  • Identify and assess individual data points in the AI response for accuracy and relevance.
  • Provide comments and feedback to clarify decisions or flag inconsistencies.

Language Proficiency:

  • Native level fluency in English.
  • Strong written and verbal communication skills in English.

Skills and Responsibilities

  • Assisting in the development and implementation of quality assurance policies.
  • Collaboration on project guidelines and supplemental learning materials.
  • Ensure compliance with client-specific requirements and performance standards in quality aspects of project execution.
  • Provide feedback and recommendations to PM team regarding UI design.
  • Review annotators and arbitrators weekly via the production monitoring process.
  • Review metrics and spot check individual tasks.
  • Record and flag quality issues.
  • Conduct end-of-day reporting to ensure smooth project handoffs and continuity across shifts.

Key Qualifications:

  • Located in Lousiville, KY and ability to work at client- on-site.
  • Required: Diploma and at least 2-3 years of experience in quality management, particularly in data services for AI.
  • Desired: Bachelor's degree, Linguistics or other related field of study
  • Experience writing data-labeling project guidelines and materials (or similar work in another field).
  • Ability to create useful and impactful insights for annotators and clients.
  • Basic familiarity with Microsoft Office 365 including Outlook, Excel, and PowerPoint.
  • General knowledge of online communication
  • Excellent communication both written and spoken.
  • Collaborative and solution focused.
  • Confidence and the ability to give/take feedback.
  • Ability to follow project directions and perform time bound tasks accurately and efficiently.
  • Ability to maintain quality while performing repetitive tasks.
  • Detail-oriented and problem-solving mindset.
  • Organized and focused enough to work independently as a role player within a team environment.

Availability:

  • Minimum of 30 hours per week.
  • Willingness to participate in training sessions and demos.

Certifications:

  • Successful completion of required certifications is mandatory.

Thanks and Regards,

Surbhi Yadav

Recruiter, Pro Integrate Consulting

New York | London | Bangalore

ISO 9001 and ISO 27001 Certified Company