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Freelance Data Labelling Jobs in New York (NOW HIRING)

Welo Data

English AI Maps Trainer

New York, NY · Remote

$20.30/hr

... Labels too small"). YOU ARE A FIT IF YOU...   * Have an eye for artistic detail and intuitive ... Freelance · Hourly rate: US$20.30 · Language: English (US) · Location: Remote · Estimated ...

Clicks Talent

Influencer & Talent Agent

New York, NY · Remote

$1.0K - $10K/mo

Remote (Work from Anywhere) Job Type: ⏰ Full-Time Freelance Contract (Flexible Hours ... Secure and negotiate high-value deals with brands, agencies, and record labels, creating successful ...

Hypebeast

Senior Creative Director

New York, NY · On-site

$140K - $160K/yr

... label client projects through Hypemaker, Hypebeast's 360 in-house cultural and creative agency ... Cultural Insights and Data * Creative & Cultural Strategy * Creative Direction * Digital Content ...

Hypebeast

Senior Creative Director

New York, NY · On-site

$140K - $160K/yr

... label client projects through Hypemaker, Hypebeast's 360° in-house cultural and creative agency ... Cultural Insights and Data * Creative & Cultural Strategy * Creative Direction * Digital Content ...

Hypebeast Limited

Senior Creative Director

Manhattan, NY · On-site

$140 - $160/hr

... label client projects through Hypemaker, Hypebeast's 360º in-house cultural and creative agency ... Cultural Insights and Data * Creative & Cultural Strategy * Creative Direction * Digital Content ...

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Freelance Data Labelling information

What is freelance data labelling?

Freelance data labelling involves working independently to annotate or tag data, such as images, text, or audio, so that it can be used to train machine learning models. As a freelancer, you may work with different clients or platforms on a project-by-project basis, labeling data according to specific guidelines. This job requires attention to detail, consistency, and sometimes domain-specific knowledge, depending on the project. Freelance data labellers often work remotely and need reliable internet access and a computer. It can be a good entry-level role for those interested in artificial intelligence and machine learning.

What are the key skills and qualifications needed to thrive as a freelance data labeller?

To thrive as a Freelance Data Labeller, you need strong attention to detail, accuracy, and basic computer literacy, often supported by a high school diploma or equivalent. Familiarity with data labelling platforms, annotation tools, and sometimes knowledge of machine learning concepts or specific project guidelines is important. Excellent time management, self-motivation, and the ability to follow instructions carefully are crucial soft skills for this role. These skills ensure high-quality labelled data, which is essential for training reliable AI and machine learning models.

What are the typical challenges faced by freelance data labellers, and how can they be effectively managed?

Freelance data labellers often encounter challenges such as repetitive tasks, tight deadlines, and ensuring high accuracy in their work. Managing these challenges involves setting clear work schedules, taking regular breaks to maintain focus, and using quality assurance tools or peer reviews to minimize errors. Additionally, effective communication with clients or project managers helps clarify labeling guidelines and expectations, which can significantly reduce misunderstandings and rework.

What is the difference between Freelance Data Labelling vs Freelance Data Annotation?

AspectFreelance Data LabellingFreelance Data Annotation
CredentialsBasic understanding of data types, attention to detailSimilar credentials, often overlapping with data labelling skills
Work EnvironmentRemote, project-basedRemote, project-based
Industry UsageUsed across AI, machine learning, and data science projectsUsed in AI, machine learning, and computer vision tasks

Both roles involve preparing data for AI models, with data labelling focusing on categorizing data and data annotation often involving adding detailed labels or annotations. The main difference lies in the scope and type of labels, but they are closely related and often overlap in freelance work.

What are the most commonly searched types of Data Labelling jobs in New York?

The most popular types of Data Labelling jobs in New York are:

What are popular job titles related to Freelance Data Labelling jobs in New York?

For Freelance Data Labelling jobs in New York, the most frequently searched job titles are:

What job categories do people searching Freelance Data Labelling jobs in New York look for?

The top searched job categories for Freelance Data Labelling jobs in New York are:

What cities in New York are hiring for Freelance Data Labelling jobs?

Cities in New York with the most Freelance Data Labelling job openings:

Freelance Data Labelling jobs near you
Infographic showing various Freelance Data Labelling job openings in New York as of August 2026, with employment types broken down into 52% Full Time, 29% Part Time, and 19% Contract. Highlights an 53% In-person, and 47% Remote job distribution.

AI Trainer - Freelance Data Annotator

Mindrift - Data annotation

New York, NY • Remote

$20/hr

Part-time

Re-posted 16 days ago

Job description

Please submit your resume in English and indicate your level of English proficiency.

Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems. Participation is project-based, not permanent employment.

What this opportunity involves

Annotation is what helps AI make sense of the world. As an annotator, you may be invited to take part in online projects such as rating AI-generated content, evaluating factual accuracy, or comparing responses - when projects are available.

While each project involves unique tasks, contributors may:

  • Carefully review provided data (text, images, or videos);
  • Label or classify content based on project guidelines;
  • Identify and flag factually incorrect, sensitive, inappropriate, or unclear material.

What we look for

This opportunity is a good fit for candidates open to part-time, non-permanent projects. Ideally, contributors will have:

  • Bachelor's degree in any discipline;
  • Minimum 1 year of experience in any professional role;
  • Logical thinking, fact-checking and reasoning abilities;
  • Strong attention to detail and ability to understand and follow complex instructions;
  • Strong communication skills, including the ability to ask clarifying questions when needed;
  • Genuine interest in technology and artificial intelligence;
  • Strong written and spoken English (C1+).

How it works 

Apply Pass qualification(s)  Join a project (when available) Complete tasks Get paid

Why this freelance opportunity might be a great fit for you

  • Take part in a part-time, remote, freelance project that fits around your primary professional or academic commitments;
  • Participate into advanced AI projects and gain valuable experience that enhances your portfolio;
  • Influence how future AI models understand and communicate in your field of expertise.

Project time expectations

For this project, tasks are estimated to require around 10-20 hours per week during active phases, based on project requirements. This is an estimate, not a guaranteed workload, and applies only while the project is active. Tasks must be submitted by the deadline and meet the listed acceptance criteria to be accepted.

Compensation

Paid per accepted task. Your rate depends on the qualification tier you reach and how efficiently you complete tasks - up to the equivalent of $20/hr. Because payment is per task, a faster pace raises your effective hourly rate. Keep in mind, quality standards must be maintained, regardless of speed.

Apply