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Remote Data Annotation Jobs in New York (NOW HIRING)

MLabs

Research Crawling Engineer

New York, NY · Remote

$100K/yr

Remote - Must have a 6 hour overlap with EST Remote | Full-time Compensation: $100K We are hiring ... Develop robust pipelines for data cleaning, deduplication, filtering, and normalization. * Build ...

MLabs

Research Crawling Engineer

New York, NY · On-site +1

$100K/yr

Remote - Must have a 6 hour overlap with EST Remote Full-time Compensation: $100K We are hiring on ... Develop robust pipelines for data cleaning, deduplication, filtering, and normalization. * Build ...

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Remote Data Annotation information

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$11

$37

$83

How much do remote data annotation jobs pay per hour?

As of Jul 18, 2026, the average hourly pay for remote data annotation in New York is $37.45, according to ZipRecruiter salary data. Most workers in this role earn between $19.18 and $48.62 per hour, depending on experience, location, and employer.

How hard is it to get hired by data annotation?

Getting hired for a remote data annotation role typically requires basic computer skills, attention to detail, and sometimes familiarity with annotation tools or platforms. Many positions are entry-level and do not require advanced education, making the application process relatively accessible, though competition can vary based on the employer and job volume.

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

To thrive as a Remote Data Annotation specialist, strong attention to detail, accuracy, and familiarity with basic data processing concepts are essential, often requiring a high school diploma or equivalent. Experience using data labeling platforms, annotation tools (such as Labelbox or Supervisely), and sometimes familiarity with spreadsheet software may be required. Excellent time management, communication skills, and the ability to work independently are valuable soft skills in this remote role. These skills are vital to ensure that data annotations are consistent, precise, and delivered on schedule, which directly impacts the quality of AI and machine learning outcomes.

How to make $1000 a week remote?

Remote data annotation jobs typically pay per task or hour, with earnings varying based on experience, accuracy, and the complexity of the data. To make $1000 a week, you need to work consistently, often requiring 20-40 hours depending on pay rates, which can range from a few cents to several dollars per annotation. Building skills in specific tools and maintaining high accuracy can help increase your earning potential in this field.

What are the typical daily tasks for someone working in Remote Data Annotation?

Daily tasks for a Remote Data Annotation role usually involve reviewing and labeling large volumes of data—such as images, audio clips, text, or video—according to specific project guidelines. You will use specialized annotation tools to identify objects, transcribe content, categorize information, or tag relevant features to support machine learning projects. Communication with project managers or quality assurance teams may be necessary for feedback and clarity on guidelines. Most roles also require regular self-checks for accuracy and the ability to meet productivity quotas or deadlines. This structure allows for a combination of focused individual work and occasional team collaboration to ensure project goals are met.

How can I make 2000 a week working from home?

Remote data annotation jobs can pay between $10 and $20 per hour, so earning $2000 weekly would require working approximately 100 to 200 hours. Increasing income may involve taking on multiple projects, improving accuracy to access higher-paying tasks, or gaining specialized skills in areas like medical or AI data annotation. Consistent work and efficient time management are essential to reach this income level.

What is a Remote Data Annotation job?

A Remote Data Annotation job involves labeling, tagging, or categorizing data (such as images, text, audio, or video) to help improve machine learning models. This work is typically done from home using specialized annotation tools provided by employers. Accuracy and attention to detail are essential, as the quality of annotations directly impacts AI model performance. Many companies hire remote annotators on a freelance, part-time, or contractual basis.

Does data annotation actually pay?

Data annotation jobs typically pay hourly or per task rates, with compensation varying based on complexity and platform. Many remote data annotation roles offer competitive pay, especially for experienced annotators using tools like labeling software, and some positions provide consistent income. However, pay rates can differ widely across companies and projects, so it is important to research specific opportunities.
What are the most commonly searched types of Data Annotation jobs in New York? The most popular types of Data Annotation jobs in New York are:
What are popular job titles related to Remote Data Annotation jobs in New York? For Remote Data Annotation jobs in New York, the most frequently searched job titles are:
What job categories do people searching Remote Data Annotation jobs in New York look for? The top searched job categories for Remote Data Annotation jobs in New York are:
What cities in New York are hiring for Remote Data Annotation jobs? Cities in New York with the most Remote Data Annotation job openings:
Remote Data Annotation jobs near you
Infographic showing various Remote Data Annotation job openings in New York as of July 2026, with employment types broken down into 47% Full Time, 20% Part Time, and 33% Contract. Highlights an 100% Remote job distribution, with an average salary of $77,903 per year, or $37.5 per hour.

Research Crawling Engineer

MLabs

New York, NY • Remote

$100K/yr

Other

Re-posted 21 days ago

Job description

Location: Remote - Must have a 6 hour overlap with EST

Remote | Full-time

Compensation: $100K

We are hiring on behalf of our client who is a technical infrastructure firm specializing in the delivery of massive-scale web data to organizations developing advanced artificial intelligence models. The organization supports high-capacity bandwidth-sharing networks and operates a distributed crawler capable of accessing high-quality public web data at a global scale. Additionally, the team has engineered sophisticated pipelines for the ingestion, segmentation, and annotation of billions of multimedia files, facilitating dataset creation for frontier research labs.

The organization operates as a lean, technical team that prioritizes speed and direct execution. As a Research Crawling Engineer, the successful candidate will design and operate large-scale web data acquisition systems. This role encompasses distributed systems, scraping infrastructure, and data pipelines, focusing on providing high-quality inputs for research and model development.

Key Responsibilities

  • Construct and maintain large-scale web crawlers across diverse domains.
  • Design high-throughput, fault-tolerant systems for data collection, managing volumes ranging from millions to billions of URLs per day.
  • Navigate anti-bot systems, rate limits, and dynamic, JavaScript-heavy websites.
  • Develop robust pipelines for data cleaning, deduplication, filtering, and normalization.
  • Build and maintain datasets specifically structured for research and machine learning model training.
  • Monitor and optimize crawl performance, coverage, and data quality through rapid iteration.
  • Collaborate with research teams to ensure data collection efforts align with modeling requirements.
  • Optimize infrastructure to ensure cost-efficiency, low latency, and reliability.

Requirements

  • Extensive programming experience in one or more of the following: Go, Rust, Python, Java, or C++.
  • Proven experience in building web crawlers or large-scale data pipelines.
  • Solid understanding of HTTP, networking protocols, and browser behavior.
  • Familiarity with distributed systems and parallel processing techniques.
  • Experience handling large datasets, ideally at the terabyte to petabyte scale.
  • Demonstrated ability to debug and maintain systems within unstable or adversarial environments.

Preferred Qualifications:

  • Experience with NLP pipelines or dataset curation for machine learning.
  • Familiarity with LLM pre-training data or retrieval systems.
  • Practical experience with headless browsers (e.g., Playwright, Puppeteer, or Chrome DevTools Protocol).
  • Knowledge of proxy systems, IP rotation, and large-scale request orchestration.
  • Background in data quality evaluation or benchmarking.
  • Experience running workloads on cloud or bare-metal infrastructure.

Benefits

  • Impactful Opportunity: Contribute to the development of a web-scale crawler and knowledge graph at the forefront of AI data accessibility.
  • High-Performance Culture: Join a lean, low-ego team that prioritizes high output and professional growth.
  • Remote Work: This position is part of a fully remote team, offering flexibility and autonomy.
  • Competitive Compensation: A package including a competitive salary, comprehensive benefits, and equity, commensurate with experience and the ability to operate at scale.

Interview Process

  1. Recruiter Coordination Call
  2. Hiring Manager Interview
  3. Founder / CEO Interview
  4. Secondary Executive Interview
  5. Final Interview


Due to the high volume of applications we anticipate, we regret that we are unable to provide individual feedback to all candidates. If you do not hear back from us within 4 weeks of your application, please assume that you have not been successful on this occasion. We genuinely appreciate your interest and wish you the best in your job search.

Commitment to Equality and Accessibility:

At MLabs, we are committed to offer equal opportunities to all candidates. We ensure no discrimination, accessible job adverts, and providing information in accessible formats. Our goal is to foster a diverse, inclusive workplace with equal opportunities for all. If you need any reasonable adjustments during any part of the hiring process or you would like to see the job-advert in an accessible format please let us know at the earliest opportunity by emailing human-resources@mlabs.city.

MLabs Ltd collects and processes the personal information you provide such as your contact details, work history, resume, and other relevant data for recruitment purposes only. This information is managed securely in accordance with MLabs Ltd's Privacy Policy and Information Security Policy, and in compliance with applicable data protection laws. Your data may be shared only with clients and trusted partners where necessary for recruitment purposes. You may request the deletion of your data or withdraw your consent at any time by contacting legal@mlabs.city.

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