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Data Labeler Remote Jobs in Colorado (NOW HIRING)

Annotate, categorize, or label text, audio, images, video, or other data where required. * Provide ... Fully remote in United States with complete schedule flexibility  * Employment Type: Freelance

Senior Manager, Data Security

Denver, CO · On-site +1

$117K - $161K/yr

This role is remote-friendly within North America. For those who prefer in-office or hybrid work ... labeling approaches * Experience designing and operating DLP controls across endpoints, network ...

... labels without lies. Founded on one simple belief - that the ingredients in your food and ... Test and iterate. Use performance data (CTR, hook rate, CPA) and customer feedback to refine ...

... labels without lies. Founded on one simple belief - that the ingredients in your food and ... Test and iterate. Use performance data (CTR, hook rate, CPA) and customer feedback to refine ...

Facilitate the design, review, and approval of IP label text and proofs to meet specific country ... Proficiency in Microsoft applications (Word, Excel, PowerPoint, Outlook, etc.), Electronic Data ...

Senior AI Product Manager

Denver, CO · On-site +1

$130K - $171K/yr

Technical literacy regarding data pipelines, dataset curation/labeling requirements, and core model ... Reliable internet connection required during remote work periods How You'll Be Rewarded Salary ...

PVC Product Manager

Denver, CO · On-site +1

$107K - $147K/yr

The schedule of remote work will be based on business and work needs as determined by management ... Responsible for updating product technical data sheets, finished product specifications, and other ...

Remote, US (preferably in Mountain Time Zone) Employment Type:Full-Time Switchfly is hiring a ... Actively direct the data science team. Stay hands-on rather thandelegating, andsteer the team ...

Data Labeler Remote information

What does a remote data labeler do?

A remote data labeler is responsible for annotating or tagging data—such as images, videos, audio, or text—from a remote location, typically working from home. Their work helps train machine learning models by providing accurate, labeled datasets that algorithms use to learn and make predictions. Data labelers follow specific guidelines to ensure consistency and accuracy, and may use specialized software tools to complete their tasks. This role is essential in industries like artificial intelligence, self-driving cars, and natural language processing. Remote data labelers often work as freelancers or as part of distributed teams for tech companies.

What are the key skills and qualifications needed to thrive as a remote data labeler?

To thrive as a Data Labeler Remote, you need strong attention to detail, basic data analysis skills, and familiarity with data annotation processes, often supported by a high school diploma or equivalent. Proficiency with labeling platforms, annotation tools, and sometimes knowledge of spreadsheet software are typically required. Reliability, time management, and effective communication are crucial soft skills for maintaining accuracy and meeting project deadlines in a remote setting. These skills ensure high-quality, consistent labeled data, which is essential for training reliable machine learning models.

What are some common challenges faced by remote data labelers and how can they be managed?

Remote data labelers often encounter challenges such as maintaining focus during repetitive tasks, ensuring consistent annotation quality, and communicating effectively with distributed teams. To manage these, it's helpful to establish a structured work routine, take regular breaks to prevent fatigue, and use annotation guidelines provided by employers. Leveraging collaboration tools for feedback and clarification also helps maintain high-quality output and fosters a sense of connection with team members.

What is the difference between Data Labeler Remote vs Data Annotator Remote?

AspectData Labeler RemoteData Annotator Remote
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentRemote, flexible hoursRemote, flexible hours
Industry UsageCommon in AI/ML data preparationCommon in AI/ML data preparation
Job FocusLabeling data points for machine learningAnnotating data for training AI models

Both Data Labeler Remote and Data Annotator Remote roles involve preparing data for AI and machine learning projects. While the terms are often used interchangeably, Data Labeler Remote typically emphasizes labeling data points, whereas Data Annotator Remote may include more detailed annotation tasks. Both roles require similar skills and are performed remotely, making them accessible for individuals seeking flexible data-related jobs.

How much does a data labeler remote make?

Remote data labelers typically earn between $12 and $20 per hour, depending on experience, complexity of tasks, and the company. Some positions may offer additional incentives or flexible schedules, but wages generally align with entry-level data annotation roles in the industry.

Is data labeling a good career?

Data labeling is a common entry-level role in the AI and machine learning industry, involving annotating data such as images, text, or audio to train algorithms. It often offers flexible remote work options and requires attention to detail but typically has lower barriers to entry and limited career advancement without additional skills or certifications.

What are the most commonly searched types of Data Labeler jobs in Colorado?

The most popular types of Data Labeler jobs in Colorado are:

What are popular job titles related to Data Labeler Remote jobs in Colorado?

For Data Labeler Remote jobs in Colorado, the most frequently searched job titles are:

What cities in Colorado are hiring for Data Labeler Remote jobs?

Cities in Colorado with the most Data Labeler Remote job openings:

Infographic showing various Data Labeler Remote job openings in Colorado as of August 2026, with employment types broken down into 43% Full Time, and 57% Part Time. Highlights an 100% Remote job distribution.

Spanish Gen AI Trainer

Welo Data

Almont, CO • Remote

Part-time

Posted 9 days ago


Job description

What if your knowledge Spanish language could help improve the AI.  
   

WHAT YOU’LL DO  

  • Review, evaluate, and validate AI-generated content and data according to project guidelines.
  • Compare AI-generated outputs and identify the most accurate, relevant, or high-quality result.
  • Identify errors, inconsistencies, omissions, and quality issues.
  • Annotate, categorize, or label text, audio, images, video, or other data where required.
  • Provide clear written feedback or justifications for your evaluations.
  • Complete assigned tasks independently and within established timelines.
  • Follow project and client guidelines consistently and maintain a high level of accuracy.
  • Attend live office hours and training sessions to familiarize yourself with project guidelines, clarify questions, and prepare for task assignments.
     

YOU ARE A FIT IF YOU’RE…  

  • A native or near-native Spanish speaker
  • Detail-oriented with strong written language skills 
     

PROJECT DETAILS  

  • Job Title: Generative AI Analyst - Spanish (US) 
  • Location: Fully remote in United States with complete schedule flexibility  
  • Employment Type: Freelance
  • Pay Rate: 15 USD/per hour

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.