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Remote Amazon Data Annotation Jobs in Canandaigua, NY

AI Data Architect

Rochester, NY · On-site +1

$150K - $200K/yr

This can be a remote opportunity, with 2 weeks of travel into Rochester, NY per quarter What You'll ... Amazon SageMaker for ML training, Model Registry, and inference * AWS HealthLake, FHIR R4 ...

AI Data Architect

Rochester, NY · Remote

$150K - $200K/yr

This can be a remote opportunity, with 2 weeks of travel into Rochester, NY per quarter What You'll ... Amazon SageMaker for ML training, Model Registry, and inference * AWS HealthLake, FHIR R4 ...

Remote Amazon Data Annotation information

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 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 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 cities near Canandaigua, NY are hiring for Remote Amazon Data Annotation jobs?

Cities near Canandaigua, NY with the most Remote Amazon Data Annotation job openings:

Infographic showing various Remote Amazon Data Annotation job openings in Canandaigua, NY as of August 2026, with employment types broken down into 1% As Needed, 78% Full Time, 18% Part Time, and 3% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution.

Record Your Daily Routine & Get Paid - AI Training (Remote)

Mindrift - Data annotation

Rochester, NY • Remote

$10/hr

Part-time

Re-posted 6 days ago


Job description

This is a project-based opportunity on an AI training platform - not a job. No fixed hours, no commitment beyond what fits your schedule. You record, you get paid.

About the Role

We're looking for people to record point-of-view videos of everyday household activities. You mount your smartphone on your head, go about your routine, and the camera captures exactly what you see. These videos help train AI systems and robots to understand how people interact with objects in real-world environments.
Do you wash dishes every day? Vacuum the rug? Walk the dog? Fold laundry? What if you could get paid just for recording it?

Responsibilities

  • Record everyday household activities from a first-person perspective - cooking, cleaning, tidying up, folding laundry, gardening, walking the dog, and more
  • Record in your own home, yard, garage, or workspace
  • Follow short recording guidelines per session
  • Upload videos through the project app

Requirements

  • Equipment: Own or use a smartphone or alternative camera device capable of 30 FPS or greater and 1080p resolution or greater. iPhone 12 or newer, Google Pixel 6+, or Samsung Galaxy S21+ (must have a wide-angle / 0.5x lens)
  • Capture method: Mount the device at forehead or eye-level for an egocentric perspective, maintaining a downward angle to maximize hand visibility.
  • Software: Utilize the designated "D&A" application for all data capture and upload.
  • Quality control: Ensure all video footage is clear, stable, well-lit, at least 15 seconds long, and accurately depicts useful, intentional tasks without unnecessary pauses or contrived movements.

Why is this freelance opportunity a great fit for you?

Earn while you do your household chores: up to $10 per hour equivalent depending on the project

This is project-based freelance work - pick up recording sessions when they fit your schedule

Influence the future of how AI and robots understand and interact with the real world