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Text Annotation Jobs in Napa, CA (NOW HIRING)

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Review, annotate, and validate nutrition and dietary data from text, images, and meal logs ... Follow annotation guidelines while maintaining high accuracy and quality standards. * Collaborate ...

... text and audio modalities. * Engineer web-scale data pipelines and apply synthetic generation ... Coordinate and manage a human annotation workforce: author guidelines, define quality targets, and ...

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Experience working with large datasets, annotation tools, and model evaluation pipelines ... Ability to interpret unstructured data (text, transcripts, user sessions) and derive meaningful ...

... text, and 3D. We combine exabyte-scale data infrastructure, novel multimodal understanding ... Source, onboard, and manage a distributed human workforce for data annotation, curation, and ...

Experience working with large datasets, annotation tools, and model evaluation pipelines ... Ability to interpret unstructured data (text, transcripts, user sessions) and derive meaningful ...

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Text Annotation information

What are the typical day-to-day responsibilities for someone working in text annotation?

Text Annotation professionals spend much of their day reading and labeling text data according to specific guidelines, ensuring that information is correctly categorized and flagged. This can involve highlighting entities, identifying sentiments, tagging parts of speech, or annotating complex relationships within text documents. They frequently collaborate with project managers, data scientists, and quality assurance teams to clarify instructions and maintain data consistency. The role often involves independent work, but regular check-ins and feedback sessions help maintain accuracy and enhance understanding of evolving annotation requirements. This combination of independent and collaborative tasks makes the position dynamic and integral to successful AI or NLP project outcomes.

What are the key skills and qualifications needed to thrive in text annotation, and why are they important?

Strong language proficiency, attention to detail, and critical thinking are essential skills for succeeding as a Text Annotation specialist, often supported by a bachelor's degree in linguistics, computer science, or a related field. Familiarity with annotation tools like Labelbox, Prodigy, or the Amazon Mechanical Turk platform, as well as knowledge of data privacy and handling protocols, is typically required. Excellent communication, self-motivation, and the ability to focus on repetitive tasks help individuals excel in this position. These capabilities ensure high-quality, consistent data labeling for machine learning models, supporting the development of cutting-edge AI solutions.

What is a text annotation?

A Text Annotation job involves labeling and categorizing text data to help train machine learning models. Annotators add tags, metadata, or classifications to text, enabling AI systems to understand language patterns. This work is essential for applications like chatbots, search engines, and sentiment analysis. Strong attention to detail and language proficiency are key skills for this role.

What job categories do people searching Text Annotation jobs in Napa, CA look for? The top searched job categories for Text Annotation jobs in Napa, CA are:
What cities near Napa, CA are hiring for Text Annotation jobs? Cities near Napa, CA with the most Text Annotation job openings:
Infographic showing various Text Annotation job openings in Napa, CA as of July 2026, with employment types broken down into 70% Full Time, and 30% Contract. Highlights an 74% In-person, and 26% Remote job distribution.

Family Medicine / Primary Care Physician (San Francisco based) (Train AI Models Part Time!)

慨正橡扯

San Francisco, CA • On-site

$200 - $300/hr

Other

Re-posted 5 days ago


Job description

About the Role

Mercor is hiring Family Medicine / Primary Care Physicians (PCPs) on behalf of a healthcare AI partner building advanced clinical decision‑support tools. In this role, you will leverage your clinical expertise to review, annotate, and validate medical data, contributing directly to the development of safe, accurate, and explainable medical AI systems. This is an in person position based in San Francisco.

Key Responsibilities
  • Clinical Data Annotation: Review and label clinical text, EHR data, and case notes for use in AI model training. Identify and validate medical entities, diagnoses, treatment pathways, and outcomes relevant to family medicine.
  • Quality Review & Validation: Audit annotated datasets for clinical accuracy and consistency. Cross‑check outputs generated by AI models to ensure medical soundness.
  • Knowledge Contribution: Provide expert input on guidelines for annotation, taxonomy development, and edge case definitions. Collaborate with data scientists and engineers to improve AI understanding of medical context.
  • Model Evaluation & Feedback: Evaluate AI‑generated recommendations or clinical summaries, flag inaccuracies, and provide structured feedback for iterative model refinement.
  • Documentation & Training Support: Contribute to the creation of clinical documentation standards and assist in developing onboarding materials for new annotators.
Requirements
  • MD or DO degree with specialization in Family Medicine or Internal Medicine.
  • Board‑certified or board‑eligible in Family Medicine or Internal Medicine.
  • Active medical license in good standing.
  • Academic hospital experience preferred.
  • 2+ years of clinical experience in in-patient or hospitalist care settings.
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