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Remote Data Labeling Jobs in Rye, NY (NOW HIRING)

Remote Commitment: 30-40 hours/week Role Responsibilities * Review real-world data from deployed ... Label and classify key behaviors, issues, and anomalies in network data. * Help define schemas and ...

... to data privacy and sensitivity labels. * Experience installing and operating Cloudera Data ... Employee Resource Groups EEO/VEVRAA #LI-MH2 #LI-Remote

Infrastructure Deployment Engineer

New York, NY ยท On-site +1

$150K - $250K/yr

... with data center facility operations. * Act as a remote hands expert for remote engineering teams ... and labeling. * Ensure all infrastructure, including racks, servers, network devices, and storage ...

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Remote Data Labeling information

How much do data labelers make?

Data labelers typically earn between $10 and $20 per hour, depending on experience, complexity of tasks, and the platform or employer. Many remote data labeling jobs are paid per task or project, which can affect overall earnings, and some roles may require basic skills in data annotation tools or image/video labeling software.

How can I make 2000 a week working from home?

Remote data labeling jobs typically pay per task or hour, with earnings varying based on experience, efficiency, and the number of tasks completed. To make $2,000 weekly, you would need to consistently complete a high volume of labeled data, often requiring strong attention to detail and familiarity with labeling tools. Achieving this income level may also involve working multiple platforms or combining data labeling with other remote tasks.

How to make $1000 a week remote?

Remote data labeling jobs typically pay per task or hour, with earnings varying based on experience, efficiency, and the volume of work completed. To make $1000 weekly, you need to consistently complete a high number of labeled data sets, often requiring strong attention to detail and familiarity with labeling tools. Building a reputation and working with multiple platforms can help increase your income potential.

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

Remote data labelers often face challenges such as maintaining focus during repetitive tasks, managing volume-based workloads, and interpreting ambiguous data with consistency. To manage these, it's important to set up a distraction-free workspace, take regular breaks to avoid fatigue, and seek clarification from supervisors or project guidelines when uncertainties arise. Most companies provide onboarding and ongoing support to help new labelers understand annotation standards and best practices. Collaborating with remote team members via chat or project management platforms also helps maintain quality and stay connected. By being proactive and utilizing available resources, remote data labelers can maintain high accuracy and productivity.

Is data labelling a good career?

Data labeling is a common entry-level role in the AI and machine learning industries, involving annotating data to train algorithms. It offers flexible schedules and requires attention to detail, but typically has lower pay and limited advancement opportunities compared to other tech roles.

What are the key skills and qualifications needed to thrive in the Remote Data Labeling position, and why are they important?

To thrive as a Remote Data Labeling specialist, you need strong attention to detail, basic data analysis skills, and the ability to accurately tag and categorize diverse data types, often with a high school diploma or equivalent. Familiarity with data labeling platforms, annotation tools (such as Labelbox or Amazon SageMaker Ground Truth), and, occasionally, basic knowledge of data privacy standards is helpful. Time management, self-discipline, and effective remote communication are valuable soft skills in this position. These skills ensure that labeled data is accurate and reliable, supporting the success of machine learning and AI projects.

What is a Remote Data Labeling job?

A Remote Data Labeling job involves annotating or categorizing data, such as images, text, audio, or video, to train machine learning models. Workers review and tag content based on specific guidelines provided by companies. This job is typically done online from home and requires attention to detail, consistency, and sometimes specialized domain knowledge. It plays a crucial role in improving artificial intelligence systems by providing high-quality labeled data.

What cities near Rye, NY are hiring for Remote Data Labeling jobs? Cities near Rye, NY with the most Remote Data Labeling job openings:

Network Specialist - Fully Remote

Mercor

New York, NY โ€ข Remote

$50 - $70/hr

Full-time

Posted 11 days ago


Job description

About the job

Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey.

Position: Network Engineer - Data for Autonomous Systems annotation
Type: Contract
Compensation: $50โ€“$70/hour
Location: Remote
Commitment: 30โ€“40 hours/week

Role Responsibilities

  • Review real-world data from deployed networks, including logs, configs, telemetry, and event streams.
  • Label and classify key behaviors, issues, and anomalies in network data.
  • Help define schemas and structure for large-scale data pipelines.
  • Interface directly with the client team to ensure data quality and relevance.
  • Work independently and asynchronously to meet deadlines and improve AI model performance.

Qualifications

Must-Have

  • Experience working as a network engineer, ideally with enterprise networks (switches, APs, firewalls, etc.).
  • Comfort with interpreting logs, events, and time-series metrics.
  • Curiosity about how raw infrastructure data becomes machine learning input.

Application Process (Takes 20โ€“30 mins to complete)

  • Upload resume
  • AI interview based on your resume
  • Submit form

Resources & Support

  • For details about the interview process and platform information, please check: https://talent.docs.mercor.com/welcome
  • For any help or support, reach out to: support@mercor.com

PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.