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Assistant Ai Labeling Jobs (NOW HIRING)

TSMG

AI/ML Data Contributor

Oklahoma City, OK · On-site

Perform AI/ML-related tasks such as data labeling, annotation, and content evaluation * Participate ... These tools assist our recruitment team but do not replace human judgment. Final hiring decisions ...

TSMG

AI/ML Data Contributor

Milwaukee, WI · Remote

Perform AI/ML-related tasks such as data labeling, annotation, and content evaluation * Participate ... These tools assist our recruitment team but do not replace human judgment. Final hiring decisions ...

TSMG

AI/ML Data Contributor

New York, NY

Perform AI/ML-related tasks such as data labeling, annotation, and content evaluation * Participate ... These tools assist our recruitment team but do not replace human judgment. Final hiring decisions ...

TSMG

AI/ML Data Contributor

Miami, FL · Remote

Perform AI/ML-related tasks such as data labeling, annotation, and content evaluation * Participate ... These tools assist our recruitment team but do not replace human judgment. Final hiring decisions ...

TSMG

AI/ML Data Contributor

Columbia, SC · Remote

Perform AI/ML-related tasks such as data labeling, annotation, and content evaluation * Participate ... These tools assist our recruitment team but do not replace human judgment. Final hiring decisions ...

TSMG

AI/ML Data Contributor

Salt Lake City, UT · Remote

Perform AI/ML-related tasks such as data labeling, annotation, and content evaluation * Participate ... These tools assist our recruitment team but do not replace human judgment. Final hiring decisions ...

TSMG

AI/ML Data Contributor

Chicago, IL · Remote

Perform AI/ML-related tasks such as data labeling, annotation, and content evaluation * Participate ... These tools assist our recruitment team but do not replace human judgment. Final hiring decisions ...

TSMG

AI/ML Data Contributor

Salt Lake City, UT

Perform AI/ML-related tasks such as data labeling, annotation, and content evaluation * Participate ... These tools assist our recruitment team but do not replace human judgment. Final hiring decisions ...

TSMG

AI/ML Data Contributor

New Orleans, LA

Perform AI/ML-related tasks such as data labeling, annotation, and content evaluation * Participate ... These tools assist our recruitment team but do not replace human judgment. Final hiring decisions ...

TSMG

AI/ML Data Contributor

Salt Lake City, UT · Remote

Perform AI/ML-related tasks such as data labeling, annotation, and content evaluation * Participate ... These tools assist our recruitment team but do not replace human judgment. Final hiring decisions ...

TSMG

AI/ML Data Contributor

Fargo, ND

Perform AI/ML-related tasks such as data labeling, annotation, and content evaluation * Participate ... These tools assist our recruitment team but do not replace human judgment. Final hiring decisions ...

TSMG

AI/ML Data Contributor

Philadelphia, PA · Remote

Perform AI/ML-related tasks such as data labeling, annotation, and content evaluation * Participate ... These tools assist our recruitment team but do not replace human judgment. Final hiring decisions ...

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All JobsAi Labeling JobsAssistant Ai Labeling Jobs

Assistant Ai Labeling information

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$29K

$48.4K

$69.5K

How much do assistant ai labeling jobs pay per year?

As of Jul 24, 2026, the average yearly pay for assistant ai labeling in the United States is $48,396.00, according to ZipRecruiter salary data. Most workers in this role earn between $42,000.00 and $48,500.00 per year, depending on experience, location, and employer.

What's the easiest AI job to get?

Entry-level AI-related jobs like data labeling or annotation are generally the easiest to obtain, as they require minimal technical skills and often offer flexible schedules. These roles involve reviewing and tagging data to help train AI models and typically do not require advanced degrees or certifications.

What is the difference between Assistant Ai Labeling vs Data Annotator?

AspectAssistant Ai LabelingData Annotator
CredentialsHigh school diploma or equivalent; some roles may require basic technical skillsHigh school diploma or equivalent; training often provided on the job
Work EnvironmentRemote or office-based; collaborative with AI teamsPrimarily remote; focused on data labeling tasks
Industry UsageAI development, machine learning projectsData preparation for AI, machine learning, and analytics
Search & Comparison IntentUnderstanding roles supporting AI trainingData labeling and annotation tasks for AI models

Assistant Ai Labeling involves supporting AI systems by labeling data, often requiring some technical understanding. Data Annotator focuses on labeling data to prepare datasets for AI training. Both roles are essential in AI development, with overlapping skills but different focus areas.

What is an AI labeling job?

An AI labeling job involves reviewing and annotating data such as images, videos, or text to help train machine learning models. Workers typically use specialized tools to add tags or labels that enable AI systems to recognize patterns and make decisions. These jobs often require attention to detail and may be performed remotely with flexible schedules.

How to become a data labeler?

To become a data labeler, you typically need basic computer skills, attention to detail, and the ability to follow instructions. Many positions require no formal education, but familiarity with data annotation tools and understanding of the specific data type (images, text, audio) can be helpful. Some companies may require completing a training or assessment before starting the job.

What are Assistant AI Labeling jobs?

Assistant AI Labeling jobs involve reviewing, tagging, and categorizing data such as images, text, or audio to help train artificial intelligence and machine learning models. These roles are essential because accurate labeling ensures that AI systems can learn to recognize patterns and make decisions effectively. Tasks may include drawing bounding boxes around objects in images, transcribing spoken words, or classifying text according to given guidelines. The work is often done using specialized software and requires attention to detail as well as consistency. Assistant AI Labelers may work remotely or in-house for tech companies, research organizations, or data annotation firms.

What are some common challenges faced by Assistant AI Labeling professionals, and how can they be addressed?

Assistant AI Labeling professionals often encounter challenges such as maintaining consistency and accuracy when labeling large volumes of data, especially with ambiguous or subjective cases. To address these challenges, most teams implement clear annotation guidelines, regular training sessions, and peer review processes to ensure high-quality outputs. Collaboration with data scientists and project managers is also key, as open communication helps clarify uncertainties and align labeling practices with project goals. Embracing feedback and staying flexible as guidelines evolve can further enhance both the quality of work and job satisfaction in this role.

What are the key skills and qualifications needed to thrive as an Assistant AI Labeling Specialist, and why are they important?

To thrive as an Assistant AI Labeling Specialist, you need strong attention to detail, accuracy, and an understanding of data annotation practices, often supported by a high school diploma or equivalent. Familiarity with data labeling platforms, annotation tools, and sometimes basic knowledge of programming languages like Python is beneficial. Dependability, time management, and the ability to follow complex instructions are crucial soft skills for excelling in this role. These skills ensure high-quality labeled data, which is vital for training accurate and reliable AI models.

How much do data labelers typically earn?

Data labelers, including assistant AI labelers, typically earn between $10 and $20 per hour, depending on experience, complexity of tasks, and the employer. Some positions may offer project-based pay or bonuses for accuracy and efficiency.
More about Assistant Ai Labeling jobs
What cities are hiring for Assistant Ai Labeling jobs? Cities with the most Assistant Ai Labeling job openings:
What are the most commonly searched types of Ai Labeling jobs? The most popular types of Ai Labeling jobs are:
What states have the most Assistant Ai Labeling jobs? States with the most job openings for Assistant Ai Labeling jobs include:
What job categories do people searching Assistant Ai Labeling jobs look for? The top searched job categories for Assistant Ai Labeling jobs are:
Assistant Ai Labeling jobs near you
Infographic showing various Assistant Ai Labeling job openings in the United States as of July 2026, with employment types broken down into 75% Full Time, and 25% Contract. Highlights an 100% In-person job distribution, with an average salary of $48,396 per year, or $23.3 per hour.
Project Perseus \u007C Data Labeling Associate - Portuguese (Brazil) Speakers (Human-in-the-Loop AI)

Project Perseus \u007C Data Labeling Associate - Portuguese (Brazil) Speakers (Human-in-the-Loop AI)

Welo Data

Washington, DC

$34/hr

Full-time

Posted 27 days ago

Job description

Overview

Welo Data is looking for sharp, curious, and detail-oriented individuals to join our team as Data Labeling Associate.

This is not a traditional annotation role.

You’ll be working directly with cutting-edge AI systems — evaluating outputs, identifying gaps, and helping improve how these systems behave in real-world scenarios. The work sits at the intersection of data quality, model evaluation, and human judgment, where your ability to think critically matters just as much as following guidelines.

We’re looking for people who are naturally curious about AI, comfortable forming opinions, and confident in contributing to conversations with teammates, leads, and stakeholders.

Project Details

  • Job Title: Data Labeling Associate
  • Hiring in: NYC, Seattle, Bellevue, Redmond, San Francisco, Sunnyvale, Burlingame, Austin, Los Angeles, Washington DC, Chicago, Boston
  • Hours: Full-time, 40 hours per week
  • Employment Type: W2 Full-Time Employee
  • Work Authorization: Must be authorized to work in the U.S. (no visa sponsorship)
  • Pay Rate: $34/hour
  • Contract Duration: 1-year contract with possibility of extension
Important: This is a 100% onsite position — remote work is not available for this role. To be considered, candidates must be located in or able to commute to one of the following cities: New York City, Seattle, Bellevue, Redmond, San Francisco, Sunnyvale, Burlingame, Austin, Los Angeles, Washington DC, Chicago, Boston. Please only apply if you meet this location requirement.
What You’ll Do
  • Evaluate AI model outputs and provide structured, high-quality feedback
  • Perform audit-based reviews of data and model behavior — identifying patterns, edge cases, and failure modes
  • Apply guidelines thoughtfully — and flag when they don’t reflect real-world scenarios
  • Contribute to improving evaluation frameworks, not just executing them
  • Identify trends in model performance and communicate insights clearly
  • Participate in team discussions, calibrations, and stakeholder syncs
  • Partner with leads and cross-functional teams to refine quality standards
  • Document findings in a clear, concise, and actionable way
What We’re Looking For
  • Native-level language proficiency and a university degree (Bachelor’s or higher).
  • B2 or superior level of English.  
  • 1–2 years of professional writing experience with strong, structured writing skills
  • Ability to apply complex writing rules and guidelines consistently
  • Strong understanding of safety considerations in GenAI data delivery, with 2+ years of relevant experience
  • Strong critical thinking and attention to detail
  • Ability to make sound judgment calls in ambiguous situations
  • Naturally curious about AI, technology, and how systems behave
  • Comfortable speaking up, asking questions, and contributing ideas
  • Strong written and verbal communication skills
  • Ability to stay consistent while working with evolving guidelines
  • Experience in data quality, QA, annotation, or analysis is helpful — but not required
Benefits
  • Paid Vacation: 6 days
  • Paid Company Holidays: 2 days (Memorial Day and Labor Day)
  • Paid Sick Leave: accrued per applicable state law and company policy
  • Medical, Dental, and Vision Insurance (eligibility applies)
  • Health Savings Account (HSA)
  • 401(k) Retirement Plan
  • Employee Assistance Program
  • Additional voluntary benefits (life, accident, critical illness, etc.)
  • Free Gourmet Food: Free breakfast, lunch, and dinner are provided, featuring a wide variety of cuisines in multiple cafes.
  • Micro-kitchens & Snacks: Offices are stocked with free snacks and beverages, including premium coffee and La Croix.
  • Unique Campus Features: Some locations include roof-top nature parks
  • Commuter Benefits: Free transport, shuttles, and sometimes bike-to-work perks.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

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.