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Remote Data Annotator Jobs (NOW HIRING)

LILT, Inc

AI Data Expert - Spanish (US) - Remote

Experience as AI reviewer, annotator, or evaluator preferred * Comfortable working with both textual and audio/video materials * Ability to follow detailed guidelines consistently and provide clear ...

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Remote Data Annotator information

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$46K

$165K

$243.5K

How much do remote data annotator jobs pay per year?

As of Jul 1, 2026, the average yearly pay for remote data annotator in the United States is $165,018.00, according to ZipRecruiter salary data. Most workers in this role earn between $133,500.00 and $170,000.00 per year, depending on experience, location, and employer.

What is a Remote Data Annotator?

A Remote Data Annotator is a professional who labels, categorizes, or tags data—such as images, text, audio, or video—while working from a remote location. This annotated data is then used to train and improve machine learning models and artificial intelligence systems. Data annotators ensure the quality and accuracy of data, which is crucial for AI applications like self-driving cars, voice recognition, and search engines. The work can vary from simple labeling tasks to more complex categorization, depending on the project requirements.

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

To thrive as a Remote Data Annotator, you need strong attention to detail, accuracy, and a basic understanding of data labeling concepts, often supported by a high school diploma or equivalent. Familiarity with annotation platforms, data management tools, and sometimes basic coding or spreadsheet software is typically required. Excellent time management, communication, and self-motivation help you consistently meet deadlines and quality standards while working independently. These skills and qualities ensure the precise labeling of data necessary for training reliable AI and machine learning models.

What are some common challenges faced by remote data annotators, and how can they be addressed?

Remote data annotators often encounter challenges such as maintaining focus during repetitive tasks, ensuring annotation accuracy, and communicating effectively with distributed teams. To overcome these, it's helpful to establish a structured work routine, take regular breaks to prevent fatigue, and leverage collaboration tools for clear communication with project managers and peers. Additionally, staying updated with project guidelines and seeking feedback can significantly improve both productivity and annotation quality.

What is the difference between Remote Data Annotator vs Remote Data Labeler?

AspectRemote Data AnnotatorRemote Data Labeler
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentRemote, flexible hoursRemote, flexible hours
Industry UsageAI, machine learning, data scienceAI, machine learning, data science
Job FocusAnnotating complex data types (images, videos)Labeling simpler data (images, text)

Remote Data Annotators typically handle complex data annotation tasks like videos and images, requiring more detailed work. Remote Data Labelers focus on simpler labeling tasks, often involving images or text. Both roles are remote, involve similar skills, and are used in AI and machine learning industries, but differ in complexity and scope of data handled.

More about Remote Data Annotator jobs
What cities are hiring for Remote Data Annotator jobs? Cities with the most Remote Data Annotator job openings:
What are the most commonly searched types of Data Annotator jobs? The most popular types of Data Annotator jobs are:
What states have the most Remote Data Annotator jobs? States with the most job openings for Remote Data Annotator jobs include:
What job categories do people searching Remote Data Annotator jobs look for? The top searched job categories for Remote Data Annotator jobs are:
Remote Data Annotator jobs near you
Infographic showing various Remote Data Annotator job openings in the United States as of June 2026, with employment types broken down into 46% Part Time, 8% Temporary, and 46% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $165,018 per year, or $79.3 per hour.

Physician Annotator - Nuclear Medicine Clinical AI (Part-Time/Contract)

NUC S.A.I.

New York, NY • On-site, Remote

Contractor

Posted 10 days ago

Job description

About Us
Nucs AI is a pioneering MedTech startup focused on transforming prostate cancer care through advanced AI-driven software solutions. Our mission is to deliver personalized treatment options that enhance patient outcomes and streamline clinical workflows. We collaborate with leading medical institutions and pharmaceutical companies globally to achieve groundbreaking results in patient care.
Role Overview
Nucs AI is entering a significant phase of growth as we expand our capabilities across nuclear molecular imaging and broaden the clinical applications of our AI-driven products. As we scale, we are strengthening our clinical annotation and validation efforts to ensure our models remain accurate, relevant, and tightly aligned with real-world oncology care. To support this expansion, we are seeking an experienced Physician Annotator to play a critical role in the development and continuous improvement of our clinical AI solutions.
This role combines hands-on nuclear medicine imaging study review, structured clinical annotation, and thoughtful product feedback to ensure AI models are clinically accurate, reliable, and aligned with real-world care delivery. The Physician Annotator will serve as a key bridge between clinical practice, data science, and product teams - bringing practical expertise to annotation standards, model validation, workflow evaluation, and performance refinement.
As part of a fast-moving, clinically grounded AI team, you will directly contribute to how advanced imaging technologies are translated into trusted tools that support physician decision-making and improve cancer care delivery at scale.
Key Responsibilities
Clinical Expertise
  • As a subject matter expert contribute to the development and refinement of annotation protocols and clinical guidelines for different use cases.
  • Identify edge cases, ambiguities, and potential sources of bias in clinical data and model behavior
  • Participate in applied clinical AI research, including hypothesis development and evaluation of model performance.
  • Assist in generating research insights that may inform internal studies, publications, or regulatory documentation

Clinical Annotation & Validation
  • Perform reviews of nuclear medicine imaging exams and provide clinical insight and annotations to support AI model training and refinement. Clinical review tasks include review of studies with and without AI assistance for identification and delineation of areas of interest on a variety of nuclear medicine images (e.g., FDG, PSMA-PET/CT, SPECT) with precision and accuracy.
  • Validate AI outputs for clinical accuracy, safety, and relevance across defined use cases.
  • Review model errors and edge cases; provide structured clinical insights to improve performance.
  • Advise on clinically meaningful metrics, thresholds, and evaluation criteria.

Strategic product feedback
  • Provide concise, actionable clinical feedback on product features and workflows.
  • Advise product teams on feature prioritization based on clinical impact, risk, and feasibility.
  • Support retrospective and prospective analyses to assess clinical validity and real-world utility of AI models.
  • Evaluate usability and workflow integration from a clinician's perspective.

Cross-Functional Collaboration
  • Collaborate asynchronously with clinical, product, and data science teams.
  • Serve as a part-time clinical advisor supporting rapid iteration and informed decision-making.

Why Join Nucs AI
  • Work at the frontier of clinical AI: Help advance next-generation oncology tools in nuclear molecular imaging.
  • Have real clinical influence: Your work and feedback directly shape model performance, product behavior, and clinical reliability.
  • High scientific rigor: Contribute to clinically grounded development with a strong focus on safety, accuracy, and real-world validity.
  • Collaborate with a high-caliber team: Work closely with clinicians, engineers, and data scientists who move fast and value clarity.
  • Flexible by design: Part-time, contract, and fully remote with flexible hours (location restrictions may apply).
  • Mission that matters: Help improve how cancer care is delivered - at scale, and with real patient impact.

Required Qualifications
  • ABR/ABNM Board certified physician with minimum 3 or more years of experience in Nuclear Medicine (or Diagnostic Radiology with subspecialty certification in Nuclear Medicine).
  • Active, unrestricted medical license in the US.
  • Possesses demonstrated expertise in interpreting PET imaging for radioligand tracers such as FDG, PSMA, and SSTR, and in radioligand therapies.
  • Exceptional attention to detail and a commitment to producing high-quality work.

Preferred Experience
  • Prior experience with healthcare AI, digital health, or clinical informatics.
  • Experience with data annotation, clinical validation, or quality review.
  • Familiarity with ML concepts, model evaluation, or human-in-the-loop systems.
  • Experience advising on product strategy or clinical product development.

Apply