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Entry Level Ai Data Labeling Jobs in California (NOW HIRING)

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Entry Level Ai Data Labeling information

What are some common challenges faced by entry level AI data labelers, and how can they be addressed?

Entry-level AI data labelers often encounter challenges such as repetitive tasks, maintaining high accuracy under tight deadlines, and understanding complex labeling guidelines. To address these, it's important to take regular breaks to avoid fatigue, seek clarification from team leads when instructions are unclear, and leverage training resources provided by the company. Collaborating with peers and utilizing feedback can also improve efficiency and accuracy, making the role both manageable and rewarding for those starting their careers in AI.

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

AspectEntry Level Ai Data LabelingData Annotation Specialist
CredentialsBasic computer skills, no formal certification often requiredSimilar; often no formal certification, but some roles prefer training in data management
Work EnvironmentRemote or on-site, flexible hours, task-basedRemote or on-site, similar flexible environment
Industry UsageCommon in AI/ML companies, tech startupsUsed across tech, healthcare, automotive industries
Search/Comparison IntentHigh overlap, both involve labeling data for AI

Entry Level Ai Data Labeling and Data Annotation Specialist roles both involve labeling data to train AI models. While they share similar credentials and work environments, the term "Data Annotation Specialist" is often used interchangeably but may imply a broader scope or more specialized tasks. Both roles are essential in AI development and typically require minimal formal education, focusing on accuracy and attention to detail.

What is entry level AI data labeling?

Entry level AI data labeling involves tagging, categorizing, or annotating data such as images, text, audio, or video to help train artificial intelligence models. Data labelers follow specific guidelines to ensure the data is accurately marked, which is essential for machine learning algorithms to learn and make predictions. This role usually requires attention to detail, basic computer skills, and the ability to follow instructions, but typically does not require advanced technical experience. Data labeling is foundational to the development of reliable AI systems.

What are the key skills and qualifications needed to thrive as an entry level AI data labeler, and why are they important?

To thrive as an Entry Level AI Data Labeler, you need strong attention to detail, basic computer literacy, and the ability to follow specific instructions, typically with at least a high school diploma or equivalent. Familiarity with annotation tools, data labeling platforms, and sometimes spreadsheet software is commonly required. Reliability, focus, and effective communication are important soft skills that help ensure high-quality, consistent work. These skills and qualities are vital for producing accurate datasets that directly impact the performance and reliability of AI models.
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 Entry Level Ai Data Labeling jobs in California? For Entry Level Ai Data Labeling jobs in California, the most frequently searched job titles are:
What job categories do people searching Entry Level Ai Data Labeling jobs in California look for? The top searched job categories for Entry Level Ai Data Labeling jobs in California are:
What cities in California are hiring for Entry Level Ai Data Labeling jobs? Cities in California with the most Entry Level Ai Data Labeling job openings:
Entry Level Ai Data Labeling jobs near you
Infographic showing various Entry Level Ai Data Labeling job openings in California as of August 2026, with employment types broken down into 64% Full Time, 17% Part Time, 2% Temporary, and 17% Contract. Highlights an 87% In-person, and 13% Remote job distribution.

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

Welo Data

Los Angeles, CA • On-site

$34/hr

Full-time

Re-posted 14 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.