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Remote Medical Data Annotation Jobs in California

Turing

Remote Medical Specialist (MD/DO)

San Francisco, CA · On-site +1

$100 - $200/hr

... quality data, advanced training pipelines, plus top AI researchers who specialize in coding ... medical AI by ensuring these systems can handle the complexity of real clinical practice. Remote ...

Motional

Senior Full Stack Engineer

San Francisco, CA · On-site +1

$149K - $198K/yr

Collaborate closely with ML, frontend, UX, data services, data mining, and data annotation teams to ... Motional's benefits include but are not limited to medical, dental, vision, 401k with a company ...

xAI

AI Healthcare and Administration Tutor

Palo Alto, CA · On-site +1

$100/hr

In this role, you will leverage your expertise in patient care coordination, medical billing ... You will collaborate with technical teams to refine annotation tools and curate impactful data ...

General Motors

Senior AI/ML Engineer

Sacramento, CA · On-site +1

$113K - $156K/yr

Remote/Hybrid: This role is based remotely but if you live within a 50-mile radius of Sunnyvale, CA ... data annotation (pre‑labeling, autolabeling, active learning loops), helping us move from ...

General Motors

Senior AI/ML Engineer

Sunnyvale, CA · On-site +1

$122K - $168K/yr

Remote/Hybrid:This role is based remotely but if you live within a 50-mile radius of Sunnyvale, CA ... data annotation (prelabeling, autolabeling, active learning loops), helping us move from humanonly ...

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Remote Medical Data Annotation information

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

To excel as a Remote Medical Data Annotation Specialist, you need a background in medical terminology, attention to detail, and familiarity with healthcare data formats, often supported by a degree or certification in a health-related field. Proficiency with annotation tools, electronic health record (EHR) systems, and data management platforms is typically required. Strong communication, time management, and analytical thinking are essential soft skills for accurate labeling and collaboration with remote teams. These competencies ensure that annotated data is reliable and precise, which is crucial for developing effective medical AI systems and supporting clinical research.

What are some common challenges faced by remote medical data annotation specialists, and how can they be overcome?

Remote medical data annotation specialists often encounter challenges such as maintaining data accuracy, understanding complex medical terminology, and managing communication with clinical teams. To overcome these, it's important to stay up-to-date with medical guidelines, participate in regular training sessions, and use collaboration tools to clarify medical ambiguities with colleagues or supervisors. Additionally, creating a structured daily workflow and setting up a distraction-free workspace can help maintain focus and accuracy when working with sensitive healthcare data.

What is the difference between Remote Medical Data Annotation vs Remote Medical Transcription?

AspectRemote Medical Data AnnotationRemote Medical Transcription
CredentialsBasic medical knowledge, attention to detailMedical terminology knowledge, typing skills
Work EnvironmentRemote, computer-basedRemote, computer-based
Industry UsageAI training, healthcare data labelingMedical record documentation
Common Search IntentData annotation, AI training jobsTranscription, medical record jobs

Both roles are remote and involve healthcare data, but Medical Data Annotation focuses on labeling data for AI models, while Medical Transcription involves converting audio recordings into written reports. Understanding these differences helps job seekers find the right fit in the healthcare data industry.

What is remote medical data annotation?

Remote medical data annotation involves labeling or tagging medical data—such as images, text, or audio—using specialized software, all while working from a location outside of a traditional office or lab. Annotators help create high-quality datasets that are essential for training machine learning models used in medical research and diagnostics. This work can include identifying areas of interest on medical scans, categorizing patient records, or transcribing audio notes. Remote annotation roles require attention to detail, a basic understanding of medical terminology, and adherence to privacy regulations like HIPAA. The position is vital for advancing artificial intelligence in healthcare.
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 Remote Medical Data Annotation jobs in California? For Remote Medical Data Annotation jobs in California, the most frequently searched job titles are:
What job categories do people searching Remote Medical Data Annotation jobs in California look for? The top searched job categories for Remote Medical Data Annotation jobs in California are:
What cities in California are hiring for Remote Medical Data Annotation jobs? Cities in California with the most Remote Medical Data Annotation job openings:
Remote Medical Data Annotation jobs near you
Infographic showing various Remote Medical Data Annotation job openings in California as of June 2026, with employment types broken down into 59% Full Time, 16% Part Time, and 25% Contract. Highlights an 100% Remote job distribution.
Remote Medical Specialist (MD/DO)

Remote Medical Specialist (MD/DO)

Turing

San Francisco, CA • On-site, Remote

$100 - $200/hr

Contractor

Posted 4 days ago

Job description

About Us

Based in San Francisco, California, Turing is the world’s leading research accelerator for frontier AI labs and a trusted partner for global enterprises deploying advanced AI systems. Turing supports customers in two ways: first, by accelerating frontier research with high-quality data, advanced training pipelines, plus top AI researchers who specialize in coding, reasoning, STEM, multilinguality, multimodality, and agents; and second, by applying that expertise to help enterprises transform AI from proof of concept into proprietary intelligence with systems that perform reliably, deliver measurable impact, and drive lasting results on the P&L.

What does day-to-day look like:
Work with research teams to evaluate and improve how AI systems handle clinical reasoning. You'll design evaluation methods that test AI performance on real medical problems where clinical expertise makes the difference.
  • Design systematic evaluation frameworks for medical AI systems.
  • Create clinical scenarios that test AI reasoning and decision-making capabilities.
  • Build assessment methods that capture the nuance of clinical practice.
  • Identify gaps in AI medical knowledge and reasoning.
  • Collaborate with AI researchers to improve model performance.

Candidate Requirements:
  • Licensed physician in active clinical practice (any specialty).
  • Experience with clinical decision-making and evidence-based medicine.
  • Interest in how AI can support clinical practice.
  • Strong analytical and communication skills.

Why it Matters:
Help shape the next generation of medical AI by ensuring these systems can handle the complexity of real clinical practice. Remote work with flexible scheduling around your clinical commitments.

Engagement details:
  • Commitment: flexible engagement, remote working, up to 30 hrs/week.
  • Duration: 1 month, with potential extensions based on performance and fit.

About Turing
Based in San Francisco, California, Turing is the world’s leading research accelerator for frontier AI labs and a trusted partner for global enterprises deploying advanced AI systems.
Turing supports customers in two ways: first, by accelerating frontier research with high-quality data, advanced training pipelines, plus top AI researchers who specialize in coding, reasoning, STEM, multilinguality, multimodality, and agents; and second, by applying that expertise to help enterprises transform AI from proof of concept into proprietary intelligence with systems that perform reliably, deliver measurable impact, and drive lasting results on the P&L.


About Turing:

Based in San Francisco, California, Turing is the world’s leading research accelerator for frontier AI labs and a trusted partner for global enterprises deploying advanced AI systems. Turing supports customers in two ways: first, by accelerating frontier research with high-quality data, advanced training pipelines, plus top AI researchers who specialize in coding, reasoning, STEM, multilinguality, multimodality, and agents; and second, by applying that expertise to help enterprises transform AI from proof of concept into proprietary intelligence with systems that perform reliably, deliver measurable impact, and drive lasting results on the P&L.