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Home Based Medical Data Annotation Jobs in California

Abaka AI

Data Operations Engineer

Mountain View, CA · On-site

$136K - $163K/yr

... based vendors and external partners. • Strong problem-solving skills and ability to operate ... with data annotation, labeling workflows, or dataset preparation for machine learning. • ...

Abaka AI

Data Operations Engineer

Mountain View, CA · On-site

$136K - $163K/yr

... based vendors and external partners. • Strong problem-solving skills and ability to operate ... with data annotation, labeling workflows, or dataset preparation for machine learning. • ...

Abaka AI

Data Operations Engineer

Mountain View, CA · On-site

$136K - $163K/yr

... based vendors and external partners. • Strong problem-solving skills and ability to operate ... with data annotation, labeling workflows, or dataset preparation for machine learning. • ...

TSMG

AI/ML Data Contributor

Los Angeles, CA · On-site

This is a flexible, task-based role with the opportunity to participate in multiple projects over time. Responsibilities * Perform AI/ML-related tasks such as data labeling, annotation, and content ...

TSMG

AI/ML Data Contributor

Los Angeles, CA

This is a flexible, task-based role with the opportunity to participate in multiple projects over time. Responsibilities * Perform AI/ML-related tasks such as data labeling, annotation, and content ...

TSMG

AI/ML Data Contributor

Los Angeles, CA

This is a flexible, task-based role with the opportunity to participate in multiple projects over time. Responsibilities * Perform AI/ML-related tasks such as data labeling, annotation, and content ...

TSMG

AI/ML Data Contributor

Los Angeles, CA

This is a flexible, task-based role with the opportunity to participate in multiple projects over time. Responsibilities * Perform AI/ML-related tasks such as data labeling, annotation, and content ...

TSMG

AI/ML Data Contributor

Los Angeles, CA · On-site

This is a flexible, task-based role with the opportunity to participate in multiple projects over time. Responsibilities * Perform AI/ML-related tasks such as data labeling, annotation, and content ...

TSMG

AI/ML Data Contributor

Los Angeles, CA · On-site

This is a flexible, task-based role with the opportunity to participate in multiple projects over time. Responsibilities * Perform AI/ML-related tasks such as data labeling, annotation, and content ...

Sesame

Technical Program Manager, Data

San Francisco, CA · On-site

$200K - $260K/yr

Lead audio data collection and annotation efforts at Sesame. * Collaborate with research and ... Flexible spending account with employer matching up to $1,650/year (medical FSA) * Guardian ...

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All JobsHome Based Medical Data Annotation JobsHome Based Medical Data Annotation Jobs in California

Home Based Medical Data Annotation information

What are some common challenges faced by professionals working in home based medical data annotation, and how can they be managed?

One common challenge in home-based medical data annotation is maintaining accuracy and consistency when labeling complex medical images or records, as errors can impact critical healthcare outcomes. Working remotely may also lead to feelings of isolation or difficulty staying updated with annotation guidelines. To manage these challenges, it's important to establish a quiet, dedicated workspace, participate in regular virtual team meetings, and utilize provided training resources. Staying engaged with peers through communication channels and seeking feedback from supervisors can also help ensure high-quality work and ongoing professional development.

What are the key skills and qualifications needed to thrive as a home based medical data annotation specialist?

To thrive as a Home Based Medical Data Annotation Specialist, you need a solid understanding of medical terminology, attention to detail, and experience with data labeling—often supported by a background in healthcare or life sciences. Familiarity with annotation platforms, EHR systems, and relevant data security protocols is typically required, and some employers may prefer certifications in medical coding or data management. Strong organizational skills, self-motivation, and effective written communication help individuals excel in remote, deadline-driven environments. These competencies ensure accurate, high-quality data labeling that is essential for developing reliable AI systems in healthcare.

What is the difference between Home Based Medical Data Annotation vs Home Based Medical Transcription?

AspectHome Based Medical Data AnnotationHome Based Medical Transcription
Required CredentialsBasic medical knowledge, attention to detailMedical terminology, transcription skills, sometimes certification
Work EnvironmentRemote, computer-basedRemote, computer-based
Industry UsageAI training, data labeling for healthcare AI modelsConverting audio to written reports for medical records
Common Search/ComparisonYesYes

Home Based Medical Data Annotation involves labeling medical images and data to train AI systems, requiring attention to detail and basic medical knowledge. In contrast, Home Based Medical Transcription focuses on converting audio recordings into written medical reports, often needing transcription skills and familiarity with medical terminology. Both roles are remote and industry-specific, but they serve different purposes within healthcare technology and documentation.

What is home based medical data annotation?

Home based medical data annotation involves labeling and categorizing medical data, such as images, audio, or text, from the comfort of your home. Annotators help train artificial intelligence (AI) systems by identifying and marking relevant information, such as highlighting tumors in X-rays or transcribing medical notes. This role is essential for improving the accuracy and efficiency of AI tools used in healthcare diagnostics, research, and patient care. Typically, it requires attention to detail, a basic understanding of medical terminology, and familiarity with annotation tools.
What are the most commonly searched types of Medical Data Annotation jobs in California? The most popular types of Medical Data Annotation jobs in California are:
What are popular job titles related to Home Based Medical Data Annotation jobs in California? For Home Based Medical Data Annotation jobs in California, the most frequently searched job titles are:
What job categories do people searching Home Based Medical Data Annotation jobs in California look for? The top searched job categories for Home Based Medical Data Annotation jobs in California are:
What cities in California are hiring for Home Based Medical Data Annotation jobs? Cities in California with the most Home Based Medical Data Annotation job openings:
Home Based Medical Data Annotation jobs near you
Infographic showing various Home Based Medical Data Annotation job openings in California as of August 2026, with employment types broken down into 68% Full Time, 18% Part Time, and 14% Contract. Highlights an 86% In-person, and 14% Remote job distribution.

Data Operations Engineer

Abaka AI

Mountain View, CA • On-site

$136K - $163K/yr

Full-time

Re-posted 20 days ago

Job description

Job Summary:
Abaka AI is dedicated to being the world's most trusted data partner for AI companies, supporting over 1,000 industry leaders with scalable data solutions. The Data Operations Engineer will manage the internal dataset library and collaborate with various teams to ensure efficient access to data and maintain dataset quality.
Responsibilities:
• Develop and maintain a comprehensive understanding of Abaka AI’s dataset library, including data structure, quality, and applicable use cases across modalities (text, image, video, audio, 3D).
• Serve as the internal point of contact for dataset-related inquiries, providing clear and timely responses to questions from engineering, product, and business teams.
• Translate ambiguous or high-level requests into concrete dataset solutions, identifying appropriate data sources or gaps.
• Inspect and validate datasets for quality, completeness, and consistency using SQL, Python, or other tools as needed.
• Coordinate with global data teams, including teams in China, to resolve data issues, clarify requirements, and ensure timely delivery without unnecessary escalation.
• Maintain and improve internal documentation, organization, and accessibility of datasets.
• Identify inefficiencies in current workflows and propose improvements to systems, tooling, and processes that support dataset management and usage.
• Support cross-functional initiatives by providing dataset insights, technical context, and operational guidance.
Qualifications:
Required:
• Bachelor’s degree in Computer Science, Data Engineering, or a related field, or equivalent practical experience.
• 1–4 years of experience in data operations, data engineering, or a related role involving direct interaction with datasets.
• Professional proficiency in Mandarin Chinese and English is required, as this role involves frequent collaboration with China-based vendors and external partners.
• Strong problem-solving skills and ability to operate effectively in ambiguous, fast-paced environments.
• Proficiency in SQL and/or Python for data inspection, validation, and basic analysis.
• Experience working with real-world datasets, including handling data quality issues, inconsistencies, and edge cases.
• Strong communication skills, with the ability to work across technical and non-technical teams.
• High level of ownership and accountability, with the ability to manage multiple requests and priorities simultaneously.
Preferred:
• Experience with multimodal datasets (text, image, video, audio, or 3D).
• Familiarity with data annotation, labeling workflows, or dataset preparation for machine learning.
• Experience working with international teams, particularly in cross-border environments.
• Exposure to AI/ML workflows, including training, fine-tuning, or evaluation datasets.
Company:
Abaka AI provides accurate and efficient AI data services, including data collection, data cleaning, data annotation, and OTS datasets. Founded in 2021, the company is headquartered in Palo Alto, USA, with a team of 51-200 employees. The company is currently Growth Stage.

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