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Hourly Remote Data Annotation Jobs in California

Data Annotation

$50 - $60/hr

Projects are paid hourly starting at USD $50-$60 per hour, with bonuses on high-quality and high ... Proficient in financial analysis, financial modeling, data analysis, and other reasoning exercises ...

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Hourly Remote Data Annotation information

What are the key skills and qualifications needed to thrive as an Hourly Remote Data Annotation Specialist, and why are they important?

To excel as an Hourly Remote Data Annotation Specialist, you need strong attention to detail, accuracy, and familiarity with data labeling concepts, often supported by a high school diploma or equivalent. Proficiency with annotation platforms, labeling tools (like Labelbox or Supervisely), and sometimes basic knowledge of spreadsheets or image/video editing software is typically required. Reliability, time management, and clear communication are vital soft skills for succeeding in a remote, deadline-driven environment. These abilities ensure high-quality, consistent annotations that are critical for training AI models and meeting project requirements.

What are some common challenges faced by hourly remote data annotation workers and how can they be addressed?

Hourly remote data annotation workers often encounter challenges such as repetitive tasks, maintaining high accuracy, and managing time effectively without direct supervision. To address these, it's important to establish a structured daily routine, take regular breaks to prevent fatigue, and utilize any quality control guidelines provided by the employer. Staying in regular communication with team leads or project managers can also help clarify any ambiguities and ensure consistent work quality.

What is the difference between Hourly Remote Data Annotation vs Hourly Remote Data Labeling?

AspectHourly Remote Data AnnotationHourly Remote Data Labeling
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentRemote, flexible hoursRemote, flexible hours
Industry UsageCommon in AI/ML projects for training dataCommon in AI/ML projects for training data
Job FocusAdding annotations to data (e.g., bounding boxes, tags)Assigning labels to datasets for model training

Both roles involve working remotely to prepare data for machine learning models. Data annotation typically involves marking specific features within data, while data labeling involves categorizing data into predefined classes. The skills and work environment are similar, making them closely related but distinct tasks within AI data preparation.

What is hourly remote data annotation?

Hourly remote data annotation involves labeling or categorizing data, such as images, text, or audio, for use in machine learning and artificial intelligence projects. Annotators work from home and are usually paid by the hour to review and tag data according to specific guidelines provided by the employer. This work is essential for training algorithms to recognize patterns or interpret information accurately. Data annotation tasks vary and can include image classification, text categorization, or identifying objects within media. It’s a popular entry-level remote job that requires attention to detail and the ability to follow instructions closely.
What are the most commonly searched types of Remote Data Annotation jobs in California? The most popular types of Remote Data Annotation jobs in California are:
What are popular job titles related to Hourly Remote Data Annotation jobs in California? For Hourly Remote Data Annotation jobs in California, the most frequently searched job titles are:
What job categories do people searching Hourly Remote Data Annotation jobs in California look for? The top searched job categories for Hourly Remote Data Annotation jobs in California are:
What cities in California are hiring for Hourly Remote Data Annotation jobs? Cities in California with the most Hourly Remote Data Annotation job openings:
Hourly Remote Data Annotation jobs near you
Infographic showing various Hourly Remote Data Annotation job openings in California as of June 2026, with employment types broken down into 67% Full Time, and 33% Contract. Highlights an 100% Remote job distribution.

Language Model Analyst - Fully Remote | Upto $20/hr Part-time

Mercor

San Francisco, CA • Remote

$20/hr

Part-time

Posted 28 days ago

Job description

About the job

Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey.

Position: Generalist - English & Kannada
Type: Contract
Compensation: $15–$20/hour
Location: Remote

Role Responsibilities

  • Conduct fact-checking using trusted public sources and external tools.
  • Generate high-quality human evaluation data by identifying response strengths, areas for improvement, and factual inaccuracies.
  • Assess reasoning quality, clarity, tone, and completeness of responses.
  • Ensure model responses align with expected conversational behavior and system guidelines.

Qualifications

Must-Have

  • Bachelor's degree.
  • Native speaker in Kannada.
  • Significant experience using large language models (LLMs).
  • Excellent writing skills in English.
  • Strong attention to detail.
  • Background or experience in domains requiring structured analytical thinking.

Preferred

  • Prior experience with RLHF, model evaluation, or data annotation work.
  • Experience writing or editing high-quality written content.
  • Experience comparing multiple outputs and making fine-grained qualitative judgments.

Application Process (Takes 20–30 mins to complete)

  • Upload resume
  • AI interview based on your resume
  • Submit form

Resources & Support

  • For details about the interview process and platform information, please check: https://talent.docs.mercor.com/welcome
  • For any help or support, reach out to: support@mercor.com

PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.