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Manager Data Annotation Ai Content Writer Jobs in Minnesota

No prior experience in AI is required -- your domain knowledge is what matters. This opportunity is ... Exceptional written and verbal communication skills, with demonstrated experience in legal content ...

New

No prior experience in AI is required -- your domain knowledge is what matters. This opportunity is ... Exceptional written and verbal communication skills, with demonstrated experience in legal content ...

New

No prior experience in AI is required -- your domain knowledge is what matters. This opportunity is ... Exceptional written and verbal communication skills, with demonstrated experience in legal content ...

New

Imaging Tech II - Non-Exempt

MN · On-site +1

$38 - $43/hr

Data Annotation * ECG Nice to Have: * IBHRE certification HM's Top Needs: * CCI CRAT or CCT ... for AI development purposes. * Deliver annotation projects assigned and work with other ...

Ensuring data products are designed to support AI applications , machine learning, intelligent ... Create dashboards, reports, or BI content * Operate as a project manager without engineering ...

Ensuring data products are designed to support AI applications , machine learning, intelligent ... Create dashboards, reports, or BI content * Operate as a project manager without engineering ...

Technical Writer

Eagan, MN · On-site +1

$65K - $85K/yr

Manage content organization and governance within multiple knowledgebases, including navigation ... Utilize AI-assisted tools, such as generative AI and Copilot, to support and accelerate content ...

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Manager Data Annotation Ai Content Writer information

Is data annotation AI a legit company?

Data annotation for AI is a common service provided by many reputable companies that specialize in labeling data for machine learning models. When evaluating a specific company, it is important to check for verified reviews, industry reputation, and transparent business practices to determine legitimacy.

What is the difference between Manager Data Annotation Ai Content Writer vs Data Annotation Specialist?

AspectManager Data Annotation Ai Content WriterData Annotation Specialist
CredentialsBachelor's degree in relevant field, experience in AI content creationHigh school diploma or equivalent, training in data annotation tools
Work EnvironmentTeam management, project oversight, collaboration with AI developersData labeling tasks, working with annotation tools, individual or team-based
Industry UsageAI development companies, tech firms, content creation agenciesAI companies, data labeling firms, machine learning teams
Search & Comparison IntentUnderstanding managerial roles in AI content creationHands-on data annotation tasks and skills

The Manager Data Annotation Ai Content Writer oversees annotation projects and manages teams, focusing on strategy and quality control. In contrast, a Data Annotation Specialist performs the actual labeling work, ensuring data accuracy. Both roles are essential in AI development but differ in responsibilities and experience requirements.

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

To thrive as a Manager Data Annotation AI Content Writer, you need expertise in data annotation processes, strong written communication, and a background in linguistics, computer science, or a related field. Familiarity with annotation tools (such as Labelbox or Prodigy), project management software, and knowledge of AI/NLP frameworks are typically required, along with certifications in data science or project management being advantageous. Outstanding organizational skills, attention to detail, and the ability to lead and train diverse teams help you excel in this role. These competencies ensure high-quality annotated datasets, efficient workflow management, and the effective development of AI-powered language models.

How does a Manager Data Annotation AI Content Writer typically collaborate with cross-functional teams to ensure high-quality AI training data?

A Manager Data Annotation AI Content Writer works closely with data scientists, machine learning engineers, and project managers to define annotation guidelines, review data quality, and align content with AI model requirements. Regular meetings and feedback sessions help ensure annotated data meets project goals and standards. Additionally, this role often provides training and support to annotation teams, fostering clear communication and continuous process improvement. This collaborative approach is crucial for maintaining accuracy and consistency in AI training datasets.

How much do AI content writers make?

AI content writers, including those specializing in data annotation for AI, typically earn between $40,000 and $80,000 annually, depending on experience, location, and the complexity of tasks. Entry-level positions may start lower, while experienced writers with specialized skills can earn higher salaries or freelance rates. Compensation often includes remote work options and flexible schedules.

How hard is it to get hired by data annotation?

Getting hired as a data annotation AI content writer typically requires basic computer skills, attention to detail, and familiarity with annotation tools. Many positions are entry-level and may not require extensive experience, but strong communication skills and the ability to follow guidelines are important. Competition varies depending on the company and location, but opportunities are generally accessible for those with relevant skills and a willingness to learn.

What is a Manager Data Annotation AI Content Writer?

A Manager Data Annotation AI Content Writer is a professional who oversees teams responsible for labeling data, such as text, images, or audio, to train artificial intelligence models. In addition to managing the data annotation process, they also create, edit, and optimize content that guides AI systems in understanding language and context. This role requires both leadership and technical skills, ensuring high-quality annotated datasets and effective communication with cross-functional teams. They play a crucial part in improving the accuracy and performance of AI-driven content and applications.

How much does an AI data annotator make?

An AI data annotator typically earns between $12 and $20 per hour, depending on experience, location, and the complexity of annotation tasks. Many roles are remote and may require basic computer skills and attention to detail.
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AI Content Rater - Ukrainian Language Specialist

Welo Data

Minneapolis, MN • Remote

$29/hr

Full-time

Posted 27 days ago


Job description

Job Title: AI Content Rater - Ukrainian Fluency

What if your expertise in Ukrainian language and writing could help improve the next generation of AI systems used by millions of people worldwide?

WHAT YOU’LL DO

  • Evaluate AI-generated responses for accuracy, grammar, and cultural relevance
  • Identify issues and provide high-quality rewritten responses
  • Create natural prompts and responses in Ukrainian to improve conversational AI datasets

YOU ARE A FIT IF YOU’RE…

  • Fluency in Ukrainian

PROJECT DETAILS

  • Location: Remote (Worldwide)
  • Employment Type: Freelance
  • Language: Ukrainian (Fluent)
  • Estimated Commitment: 8–10 hours

BENEFITS

  • $29.00 USD per hour
  • Fully remote and flexible work arrangement

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.