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Remote Amazon Data Annotation Jobs in Bayonne, NJ

Zenlaw

Data Scientist (Remote)

New York, NY · On-site +1

Run data analysis on our dataset to design potential rules for annotation. * Improve the ... Due to the remote nature of this role, we are unable to provide visa sponsorship.

Envision Horizons

Sr. Amazon Ads Account Manager

New York, NY · On-site +1

$100K - $110K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Analyze performance data to uncover insights, guide strategic pivots, and drive continuous ... Fully remote culture, with collaborative hubs in New York, Boston, Chicago, Denver, Salt Lake City ...

Shaped

Data Engineer

Brooklyn, NY · Remote

$130K - $200K/yr

Google, Amazon, Uber, Dropbox etc...). Our team comes from Meta, Google, Apple and Uber. We're a remote team but have a small office in Brooklyn, New York. We are looking for a data engineer to ...

Mondo

Amazon DSP, Sr Spec

Manhattan, NY · Remote

$35 - $40/hr

  • Medical

  • Dental

  • Vision

  • Retirement

Remote (US Based) Start Date Is: ASAP Duration: 3 Month Contract (option to extend or convert ... Data & Measurement Data-Driven: * Analyze campaign data to extract actionable insights and support ...

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All JobsAmazon Data Annotation JobsRemote Amazon Data Annotation JobsRemote Amazon Data Annotation Jobs in Bayonne, NJ

Remote Amazon Data Annotation information

What is the difference between Remote Amazon Data Annotation vs Remote Mechanical Turk Worker?

AspectRemote Amazon Data AnnotationRemote Mechanical Turk Worker
CredentialsNo formal certifications required, but attention to detail helpsNo formal certifications required, basic task understanding needed
Work EnvironmentRemote, flexible hours, online platformRemote, flexible hours, online micro-task platform
Employer & IndustryAmazon, e-commerce, AI training dataVarious clients, data labeling, surveys, research

Remote Amazon Data Annotation involves labeling data specifically for Amazon's AI and e-commerce needs, often requiring attention to detail. Mechanical Turk workers perform a variety of micro-tasks across industries. While both are remote and flexible, data annotation is more specialized for AI training, whereas Mechanical Turk offers broader task types.

What are common challenges faced by remote Amazon data annotation specialists and how can they be addressed?

Remote Amazon Data Annotation specialists often encounter challenges such as maintaining consistency and accuracy across large volumes of data, managing repetitive tasks, and staying engaged while working independently. To address these, it's important to develop a strong attention to detail, utilize quality control tools provided by the platform, and take regular breaks to minimize fatigue. Additionally, staying connected with your team through regular check-ins and feedback sessions can help ensure alignment on annotation guidelines and improve overall performance.

What is a remote Amazon data annotation job?

Remote Amazon Data Annotation jobs involve labeling, categorizing, or tagging data such as images, text, or audio to help train machine learning models used by Amazon. Employees work from home using specialized tools to ensure accuracy and consistency in the data provided. These roles often require attention to detail, the ability to follow guidelines, and sometimes specific domain knowledge depending on the project. Data annotation is essential for improving the performance of AI systems in tasks like product recommendations, voice recognition, and search algorithms. These roles may be full-time, part-time, or project-based, offering flexibility for remote workers.

What skills and qualifications are needed for a remote Amazon data annotation specialist?

To thrive as a Remote Amazon Data Annotation Specialist, you need strong attention to detail, analytical thinking, and familiarity with data labeling concepts, often supported by a high school diploma or relevant experience. Competence with web-based annotation tools, cloud-based platforms, and sometimes Amazon-specific data systems is typically required. Diligence, consistency, effective communication, and the ability to work independently are valuable soft skills in this role. These skills and qualities are important to ensure high-quality, accurate data labeling that supports effective machine learning and AI model development.
What are popular job titles related to Remote Amazon Data Annotation jobs in Bayonne, NJ? For Remote Amazon Data Annotation jobs in Bayonne, NJ, the most frequently searched job titles are:
What job categories do people searching Remote Amazon Data Annotation jobs in Bayonne, NJ look for? The top searched job categories for Remote Amazon Data Annotation jobs in Bayonne, NJ are:
What cities near Bayonne, NJ are hiring for Remote Amazon Data Annotation jobs? Cities near Bayonne, NJ with the most Remote Amazon Data Annotation job openings:
Remote Amazon Data Annotation jobs near you
Infographic showing various Remote Amazon Data Annotation job openings in Bayonne, NJ as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

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

NUC S.A.I.

New York, NY • On-site, Remote

Contractor

Re-posted 22 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