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Hourly Remote Data Annotation Jobs in California

... annotation or labels for ML development. * Analyze complex data/ML problems and break them into ... This is a remote friendly position for both US and Canada based candidates. * On-site desk-space is ...

Senior Director, AI

Bodega Bay, CA · On-site +1

$257K - $402K/yr

Secure and allocate funding for specialized datasets and data annotation services. * Evaluate and ... This is a fully remote role with the option to work hybrid if a commutable distance from our Salem ...

Remote Job Overview We are seeking experienced Medical Coders to contribute their healthcare coding ... Familiarity with digital annotation tools or healthcare data projects is a plus. * Commitment to ...

Remote Job Overview We are seeking experienced Medical Coders to contribute their healthcare coding ... Familiarity with digital annotation tools or healthcare data projects is a plus. * Commitment to ...

Remote Job Overview We are seeking experienced Medical Coders to contribute their healthcare coding ... Familiarity with digital annotation tools or healthcare data projects is a plus. * Commitment to ...

Remote Job Overview We are seeking experienced Medical Coders to contribute their healthcare coding ... Familiarity with digital annotation tools or healthcare data projects is a plus. * Commitment to ...

San Francisco, CA About the Role HumanSignal specializes in operationally complex, multimodal data collection and annotation -- delivering the datasets that frontier AI research requires and remote ...

Showing results 21-40

Hourly Remote Data Annotation information

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 key skills and qualifications needed to thrive as an hourly remote data annotation specialist?

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 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:

Infographic showing various Hourly Remote Data Annotation job openings in California as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 12% Part Time, 2% Temporary, and 3% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution.

AI Software Engineer Expert - Remote

YO AI Labs

San Francisco, CA • Remote

$100 - $200/hr

Part-time

Posted 6 days ago


Job description

Job Title: AI Software Engineering Domain Remote

Job Type: Contractor (Part-Time)
Location: Remote

Job Overview

We are seeking experienced AI Software Engineering Domain Experts to contribute their technical expertise to an innovative project focused on improving next-generation AI systems. In this role, you will evaluate, review, and refine AI-generated software engineering content to enhance the quality, accuracy, and reasoning of AI models. No prior AI experience is required—your software engineering expertise is what matters most.

Key Responsibilities
  • Analyze, review, and improve AI-generated software engineering content for technical accuracy and clarity.
  • Create, refine, and evaluate prompts to improve AI-generated technical outputs.
  • Conduct rubric-based evaluations of AI model responses, providing detailed quality feedback.
  • Draft and edit technical documentation, architecture documents, RFCs, design specifications, and engineering proposals.
  • Perform independent research and fact-checking to validate technical information.
  • Interpret and annotate technical data to support AI model training and evaluation.
  • Collaborate remotely with cross-functional teams to deliver high-quality project outcomes.
Required Skills
  • Critical Thinking
  • Analytical Reasoning
  • Quality Assurance
  • Prompt Engineering
  • AI Output Evaluation
  • Technical Documentation
  • Technical & Professional Writing
  • Content Review & Editing
  • Data Annotation
  • Fact Checking
  • Independent Research
  • Business Communication
  • Problem-Solving
  • Attention to Detail
Preferred Qualifications
  • 3+ years of professional experience as a Software Engineer, Senior Software Engineer, Staff Engineer, Technical Lead, Engineering Manager, Solutions Architect, or similar role.
  • Experience authoring or reviewing technical documentation, architecture documents, RFCs, design specifications, engineering proposals, postmortems, technical blogs, or code reviews.
  • Strong critical thinking, analytical reasoning, and structured problem-solving skills.
  • Excellent written communication and technical editing abilities.
  • Experience with AI coding tools or automated documentation tools is a plus but not required.
  • Advanced degree (Master's, MBA, JD, or PhD) or equivalent professional experience is preferred.