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Part Time Remote Data Labelling Jobs in California

YO AI Labs

AI Data Science Expert - Remote

Palo Alto, CA · Remote

$100 - $200/hr

Contractor (Part-Time) Location: Remote Job Overview We are seeking experienced AI Data Science Domain Experts to contribute their expertise to an innovative project focused on advancing next ...

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All JobsData Labelling JobsPart Time Remote Data Labelling JobsPart Time Remote Data Labelling Jobs in California

Part Time Remote Data Labelling information

What is a part time remote data labelling job?

A part time remote data labelling job involves annotating or tagging data—such as images, text, or audio—from your own location, typically using specialized software provided by employers. The role is essential for training machine learning models, as accurate labels help computers learn to recognize patterns. These jobs are often flexible, allowing you to set your own hours and work from anywhere with an internet connection. No advanced technical skills are usually required, but attention to detail is important.

What are the key skills and qualifications needed to thrive as a part time remote data labelling specialist?

To excel as a Part Time Remote Data Labelling specialist, you need strong attention to detail, basic computer literacy, and a solid understanding of data privacy and handling protocols, often requiring a high school diploma or equivalent. Familiarity with annotation platforms, spreadsheet software, and sometimes specific data labelling tools like Labelbox or Supervisely is typically required. Reliability, time management, and clear communication are crucial soft skills for meeting deadlines and collaborating in a remote setting. These skills and qualities ensure that labelled data is accurate, consistent, and valuable for training effective machine learning models.

What are some common challenges faced by part time remote data labelling professionals, and how can they be managed?

Part-time remote data labellers often face challenges such as maintaining consistent accuracy, staying focused during repetitive tasks, and managing communication with a distributed team. To address these, it’s helpful to establish a quiet, distraction-free workspace, use productivity techniques like the Pomodoro method, and regularly review labelling guidelines to minimize errors. Leveraging communication tools and participating in team check-ins can also help clarify questions and build a sense of connection with colleagues.

What is the difference between Part Time Remote Data Labelling vs Part Time Remote Data Annotation?

AspectPart Time Remote Data LabellingPart Time Remote Data Annotation
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentRemote, flexible hoursRemote, flexible hours
Industry UsageAI, machine learning, data processingAI, machine learning, data processing
Job FocusLabeling data for training AI modelsAnnotating data for AI training

Part Time Remote Data Labelling and Part Time Remote Data Annotation are similar roles involving preparing data for AI systems. Labelling typically involves categorizing data, while annotation may include adding detailed notes or markings. Both roles require attention to detail and are performed remotely, making them suitable for flexible schedules. The main difference lies in the specific tasks, but they are often used interchangeably depending on the employer or project.

What are the most commonly searched types of Remote Data Labelling jobs in California?

The most popular types of Remote Data Labelling jobs in California are:

What are popular job titles related to Part Time Remote Data Labelling jobs in California?

For Part Time Remote Data Labelling jobs in California, the most frequently searched job titles are:

What job categories do people searching Part Time Remote Data Labelling jobs in California look for?

The top searched job categories for Part Time Remote Data Labelling jobs in California are:

What cities in California are hiring for Part Time Remote Data Labelling jobs?

Cities in California with the most Part Time Remote Data Labelling job openings:

Part Time Remote Data Labelling jobs near you
Infographic showing various Part Time Remote Data Labelling job openings in California as of August 2026, with employment types broken down into 1% As Needed, 88% Full Time, 9% Part Time, and 2% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution.

AI Data Science Expert - Remote

YO AI Labs

Palo Alto, CA • Remote

$100 - $200/hr

Part-time

Posted 9 days ago

Job description

Job Title: AI Data Science Domain Expert

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

Job Overview

We are seeking experienced AI Data Science Domain Experts to contribute their expertise to an innovative project focused on advancing next-generation AI systems. In this role, you will review, evaluate, and refine AI-generated technical and analytical content to improve model accuracy, reasoning, and overall performance. No prior AI experience is required—your data science expertise, analytical thinking, and communication skills are what matter most.

Key Responsibilities
  • Review, edit, and refine AI-generated content for accuracy, clarity, and technical relevance.
  • Develop, optimize, and evaluate prompts to improve AI model performance.
  • Conduct rubric-based assessments of AI outputs and provide structured feedback.
  • Perform independent research and fact-checking to validate technical information.
  • Annotate data and support quality assurance initiatives for AI training.
  • Interpret complex datasets and prepare clear technical reports and summaries.
  • Collaborate remotely with project teams to improve AI models and workflows.
Required Skills
  • Critical Thinking
  • Analytical Reasoning
  • Prompt Engineering
  • AI Output Evaluation
  • Quality Assurance
  • Technical Documentation
  • Technical & Report Writing
  • Content Review & Editing
  • Data Annotation
  • Data Interpretation
  • Fact Checking
  • Independent Research
  • Problem-Solving
  • Attention to Detail
Preferred Qualifications
  • 3+ years of experience in Data Science, Machine Learning, Applied AI, Statistics, Quantitative Analytics, or Data Analytics.
  • Experience producing or reviewing research papers, analytical reports, technical documentation, experiment summaries, or data-driven recommendations.
  • Strong analytical reasoning, critical thinking, and written communication skills.
  • Experience with data annotation, content review, or rubric-based evaluation is preferred.
  • Familiarity with prompt engineering, AI output evaluation, fact-checking, or RLHF is a plus.
  • Master's, MBA, PhD, or other advanced degree is preferred.