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Internship Ai Data Labeling Jobs in California (NOW HIRING)

TSMG

AI/ML Data Contributor

Los Angeles, CA · On-site

Perform AI/ML-related tasks such as data labeling, annotation, and content evaluation * Participate in remote assignments or attend on-site sessions when required * Follow project guidelines and ...

Snorkel AI

Lead Data Scientist

San Francisco, CA · Hybrid

$130K - $200K/yr

Experience with Streamlit, Snowflake Cortex, AI/data labeling, A/B testing, and two-sided marketplace or data product business models. Pay Transparency Notice: Depending on your work location, the ...

Welocalize

Lead Gen AI Analyst

Santa Clara, CA · On-site +1

$50/hr

What We're Looking For * 5+ years of experience in AI data operations, data annotation, content quality, Trust & Safety, data labeling, or similar production environments. * 3+ years of experience ...

UJET

AI Data Engineer

Los Angeles, CA · On-site

$123K - $148K/yr

We are hiring an AI Data Engineer to own the seam between "customer says yes" and "data is flowing ... internship, contract, or full-time all qualify * Daily fluency with a standard engineering workflow ...

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Internship Ai Data Labeling information

What is an AI data labeling internship?

An AI Data Labeling Internship is a temporary position where interns assist in preparing datasets for machine learning models by accurately annotating, categorizing, or tagging data such as images, text, or audio. Interns learn about the fundamentals of artificial intelligence and the importance of high-quality labeled data in training algorithms. This role is ideal for students or recent graduates interested in AI, data science, or related fields, and provides hands-on experience with data preparation and quality assurance processes.

What are the key skills and qualifications needed to thrive as an AI data labeling intern?

To thrive as an AI Data Labeling Intern, you need attention to detail, basic data analysis skills, and familiarity with data annotation concepts, often supported by a background in computer science or related fields. Experience using annotation platforms, spreadsheets, and sometimes specific labeling software is common, though formal certifications are not usually required. Strong communication, time management, and the ability to follow detailed guidelines set high performers apart in this role. These skills ensure accurate, high-quality data sets that are essential for training reliable AI models.

What are some common challenges faced during an AI data labeling internship, and how can I overcome them?

As an AI Data Labeling intern, you may encounter challenges such as maintaining high accuracy while labeling large volumes of data, understanding complex labeling guidelines, and managing repetitive tasks without losing focus. To overcome these, it's helpful to regularly review the instructions, seek feedback from your team lead, and use productivity techniques to stay engaged. Collaborating with other interns and attending team meetings can also provide valuable insights and help you address uncertainties quickly.

What is the difference between Internship Ai Data Labeling vs Data Annotation Specialist?

AspectInternship Ai Data LabelingData Annotation Specialist
Required CredentialsHigh school diploma or equivalent; some technical skillsHigh school diploma or higher; technical skills often preferred
Work EnvironmentEntry-level, training-focused, often remote or in-officeProfessional setting, may be remote or on-site, more independent
Employer & Industry UsageTech companies, AI startups, research projectsAI companies, data service providers, tech firms
Search & Comparison IntentUnderstanding entry-level roles in AI data labelingClarifying professional data annotation roles

Internship Ai Data Labeling typically refers to entry-level, training-focused positions aimed at gaining experience in labeling data for AI models. Data Annotation Specialist is a more experienced, professional role involving detailed data labeling tasks. Both roles are essential in AI development, but internships are designed for beginners, while specialists have more responsibility and expertise.

What are the most commonly searched types of Ai Data Labeling jobs in California?

The most popular types of Ai Data Labeling jobs in California are:

What are popular job titles related to Internship Ai Data Labeling jobs in California?

For Internship Ai Data Labeling jobs in California, the most frequently searched job titles are:

What job categories do people searching Internship Ai Data Labeling jobs in California look for?

The top searched job categories for Internship Ai Data Labeling jobs in California are:

What cities in California are hiring for Internship Ai Data Labeling jobs?

Cities in California with the most Internship Ai Data Labeling job openings:

Internship Ai Data Labeling jobs near you
Infographic showing various Internship Ai Data Labeling job openings in California as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 13% Part Time, and 2% Contract. Highlights an 86% Physical, 3% Hybrid, and 11% Remote job distribution.

AI/ML Data Contributor

TSMG

Los Angeles, CA • On-site

Part-time

Re-posted 11 days ago

Job description

Project Overview
We are currently hiring AI/ML Data Contributors to support a range of active and upcoming projects across the United States. In this role, you will participate in tasks that help improve machine learning models, including data labeling, content evaluation, and user-based testing.

Projects may vary in scope and format, offering both remote and in-person opportunities (such as device or VR testing). This is a flexible, task-based role with the opportunity to participate in multiple projects over time.

Responsibilities
  • Perform AI/ML-related tasks such as data labeling, annotation, and content evaluation
  • Participate in remote assignments or attend on-site sessions when required
  • Follow project guidelines and ensure high-quality task completion
  • Provide feedback and input during testing activities
  • Complete tasks within given timelines
Requirements
  • Must be based in the United States
  • Strong attention to detail and ability to follow instructions
  • Basic computer skills and familiarity with digital tools
  • Reliable internet connection and access to a computer or smartphone
  • Availability to participate in task-based work (schedule may vary)
Nice to Have
  • Previous experience in data annotation, QA, or testing
  • Interest in AI, machine learning, or emerging technologies
What We Offer
  • Paid, flexible task-based work
  • Opportunity to work on innovative AI/ML projects
  • Exposure to cutting-edge technologies (including device and VR testing)
  • Potential for ongoing project participation
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.
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