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Text Annotation Jobs in Martinez, CA (NOW HIRING)

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 ...

Technical Product Manager

San Francisco, CA · On-site +1

$140K - $180K/yr

... text, and business workflows. Troveo indexes, enriches, and packages this high-quality data into ... annotation, and downstream delivery. * Help design processing pipelines and logic tailored to ...

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Text Annotation information

What are 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.

Are data annotations still hiring?

Data annotation roles, including those for text annotation, are still in demand as companies continue to develop AI and machine learning models. These jobs often require attention to detail and familiarity with annotation tools, and they can be available as remote or part-time positions. Hiring trends depend on industry needs and project pipelines, but opportunities remain consistent in this field.

What is a text annotation job?

A text annotation job involves labeling or tagging parts of text data to help train machine learning models, especially in natural language processing tasks. Workers typically review text and add labels such as entities, sentiments, or categories using specialized tools, often working remotely with flexible schedules.

What are the key skills and qualifications needed to thrive in the Text Annotation position, 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.

Is data annotation a legit job?

Data annotation is a legitimate job that involves labeling data such as images, text, or audio to help train machine learning models. It often requires attention to detail and familiarity with annotation tools, and it can be performed remotely or in-office. Many companies hire data annotators as part of their AI development teams.

What is a Text Annotation job?

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 qualifications do you need to be a data annotator?

To be a data annotator, basic qualifications typically include a high school diploma or equivalent, strong attention to detail, and good reading and comprehension skills. Familiarity with annotation tools and the ability to follow specific guidelines are also important, while prior experience or knowledge in the relevant domain can be beneficial but is not always required.
What cities near Martinez, CA are hiring for Text Annotation jobs? Cities near Martinez, CA with the most Text Annotation job openings:
Infographic showing various Text Annotation job openings in Martinez, CA as of July 2026, with employment types broken down into 72% Full Time, and 28% 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

Posted 20 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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