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Volunteer Remote Data Labelling Jobs in California

... and remote workforce marketplaces can't. We own projects end-to-end, from scoping and protocol ... Our work spans RLHF, evals, red-teaming, and custom multimodal data creation, all powered by Label ...

We are looking for a spatial thinker with a passion for remote sensing analysis and visual ... Volunteering Paid Time Off Compensation: The US base salary range for this full-time position at ...

Lead Data Analyst

Foster City, CA · Remote

$120K - $160K/yr

We run these virtual- and private-label marketplaces in one of the nation's largest media networks ... REMOTE QuinStreet is an equal opportunity employer. We do not discriminate on the basis of race ...

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Volunteer Remote Data Labelling information

What is the difference between Volunteer Remote Data Labelling vs Remote Data Annotation?

AspectVolunteer Remote Data LabellingRemote Data Annotation
CredentialsNone typically required, basic computer skillsOften similar, may require familiarity with annotation tools
Work EnvironmentRemote, flexible, volunteer basisRemote, paid or unpaid depending on the role
Industry UsageUsed in AI training, research projectsUsed in AI, machine learning, and data science projects

Volunteer Remote Data Labelling involves unpaid tasks where individuals label data for research or nonprofit projects, often with minimal credentials. Remote Data Annotation typically refers to paid roles with similar tasks but may require some familiarity with annotation tools. Both roles are remote and support AI development, but volunteer labelling is unpaid and driven by altruism, while data annotation can be paid and more structured.

What are data labelling and annotation jobs?

Data labelling and annotation jobs involve reviewing and marking data such as images, text, or audio to help train machine learning models. These tasks require attention to detail and often use specialized tools or platforms, and they are typically performed remotely with flexible schedules.

What does a volunteer remote data labelling specialist do?

A volunteer remote data labelling specialist reviews and annotates data such as images, audio, or text to help train machine learning models. They typically use specialized tools and follow guidelines to ensure accurate and consistent labels, working independently from a remote location. This role supports AI development and often requires attention to detail and basic understanding of data annotation processes.

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

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

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

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

Healthcare Workflow Specialist - Fully Remote | Upto $80/hr

Mercor

San Francisco, CA • Remote

$80/hr

Full-time

Re-posted 15 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: Registered Nurses (Data labelling and training)
Type: Contract
Compensation: $60–$80/hour
Location: Remote

Role Responsibilities

  • Review and assess clinical documentation for accuracy, completeness, and quality.
  • Analyze healthcare workflows and recommend process improvements.
  • Interpret patient records and clinical notes to support product development.
  • Identify documentation gaps, inconsistencies, and edge cases.
  • Collaborate with product, engineering, and operations teams to refine AI-driven healthcare tools.
  • Ensure adherence to healthcare regulations, policies, and best practices.

Qualifications

Must-Have

  • Active Registered Nurse (RN) license.
  • 3–5+ years of clinical nursing experience.
  • Strong understanding of clinical documentation and healthcare workflows.
  • Experience working with EHR systems (Epic, Cerner, Meditech, etc.).
  • Excellent analytical, communication, and problem-solving skills.

Preferred

  • Experience in CDI, case management, utilization review, or quality improvement.
  • Exposure to healthcare technology, AI tools, or digital health products.
  • Ability to collaborate effectively with cross-functional teams.

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.