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Data Annotation Manager Jobs in West Virginia (NOW HIRING)

Senior AI/ML Engineer

Charleston, WV · On-site +1

$101K - $139K/yr

We partner closely across AI/ML engineers , Product Operations , Product Management , Data Science ... data annotation (pre‑labeling, autolabeling, active learning loops), helping us move from ...

Within LDC, the Annotation/Collection group creates labeled data sets for high-stakes, externally ... Work withproject managers andsoftware developers to design,specifyand test user interfaces, data ...

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Data Annotation Manager information

See West Virginia salary details

$24K

$75.2K

$133.2K

How much do data annotation manager jobs pay per year?

As of Jun 14, 2026, the average yearly pay for data annotation manager in West Virginia is $75,206.00, according to ZipRecruiter salary data. Most workers in this role earn between $51,100.00 and $97,200.00 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 West Virginia? The most popular types of Data Annotation jobs in West Virginia are:
What are popular job titles related to Data Annotation Manager jobs in West Virginia? For Data Annotation Manager jobs in West Virginia, the most frequently searched job titles are:
Infographic showing various Data Annotation Manager job openings in West Virginia 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 $75,206 per year, or $36.2 per hour.
Entertainment Media Content Writer (Remote in the United States)

Entertainment Media Content Writer (Remote in the United States)

Welo Data

Charleston, WV • Remote

$40/hr

Contractor

Posted 10 days ago


Job description

Overview  

Are you a seasoned writer with a passion for storytelling, cinema, and the professional media landscape? We are seeking an experienced and versatile Creative Content Writer to join our team.

In this role, you will be responsible for crafting high-quality, engaging content that resonates with audiences across the TV and film industry.  You will leverage your expertise in professional writing to develop narratives that maintain a sophisticated corporate persona while remaining creatively inspired. Your ability to perform research and apply critical thinking will ensure our content remains authoritative and impactful in the ever-evolving world of entertainment and pop culture at large.

What you will do: 

  • Review contributor evaluations of model-generated responses to ensure adherence to project-specific guidelines and rubric dimensions.
  • Verify that contributors consistently apply all instructions, constraints, and evaluation criteria when assessing model responses.
  • Confirm that contributors accurately identify factual errors, hallucinations, or missing information in model responses, ensuring evaluations reflect whether responses fulfill the user query.
  • Ensure contributor-selected options align appropriately with rubric dimensions and are justified by the evidence present in the model response.
  • Review open-text comments provided by contributors, ensuring they identify areas of opportunity, weaknesses, or limitations that may not have been captured by rubric criteria.
  • Provide detailed feedback on contributor performance, highlighting areas for improvement and ensuring evaluations are consistently high-quality.

Project Details: 

  • Location: Remote in the US
  • Job Type: Freelance
  • Pay Rate: $40 USD /hour
  • Expected capacity: 20 hours per week
  • Start date: As soon as possible
  • Hiring in: Alabama, Colorado, Delaware, Florida, Georgia, Indiana, Kansas, Kentucky, Missouri, Montana, Nevada, New Hampshire, New Mexico, North Carolina, Ohio, Oklahoma, Oregon, Pennsylvania, South Carolina, Tennessee, Texas, Utah, Virginia, West Virginia, and Wisconsin.

Requirements: 

  • Proven Expertise in one or more of the following areas (relevant degrees such as a Bachelor’s in Film and Media Studies, Journalism, or related fields are highly preferred):
  • Film and media studies
  • Entertainment journalism, film criticism, or media commentary
  • Content analysis focused on movies, TV series, and streaming platforms
  • Entertainment blogging, reviewing, or significant contributions to pop culture communities
  • Pop culture commentary and media writing

Strong familiarity with:

  • Narrative structures, character arcs, and continuity across cinematic universes and episodic storytelling.
  • Contextual and cultural references specific to entertainment media.

Proven experience in:

  • Roles involving AI data annotation, content quality review, search quality rating, or similar.
  • Evaluating content using structured grading criteria and providing thoughtful, constructive feedback.
  • Performing in-depth fact-checking and identifying factual inaccuracies in content.
  • Meticulous attention to detail and the ability to identify nuanced or subtle issues in contributor evaluations.
  • Ability to work independently and manage workflows effectively in a remote environment.
  • Familiarity with data annotation platforms and model evaluation tools.

Preferred Qualifications:

  • Prior experience conducting quality audits, content review, or evaluation in an entertainment-related capacity.
  • In-depth understanding of current trends in pop culture and the entertainment industry.
  • Ability to interpret prompts referencing specific storylines, characters, franchises, and broader entertainment contexts.
  • Active use of major streaming platforms and strong familiarity with their catalog of films, television series, and original content

Working at Welo Data

What to expect from working at Welo Data

From Welo Data

About Welo Data, in their own words

From Welo Data

Welo Data is a global AI data services company powering the next generation of AI. We build, annotate, and validate the training datasets that make AI models accurate, safe, and ready for the real world — across languages, cultures, and domains.

Our team of experts spans the globe, combining deep technical knowledge with a human-centered approach. If you want your work to shape how AI understands the world, you'll find your place here.

Diversity and inclusion statement

From Welo Data

Our Strength is derived from Winning Together. Welo Data is unequivocally committed to developing and fostering a workplace and organizational culture that values the diversity of thought and perspective delivered by a diverse global workforce operating within an inclusive organization.