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Freelance Machine Learning Data Annotation Jobs in New York

Welocalize, Inc.

Data Quality Analyst

New York, NY · On-site

Modify and refine machine learning data creation, annotation, and rating guidelines. Model Training and Evaluation: * Initiate model training processes using internal tools and command-line ...

Welocalize, Inc.

Data Labeling Associate

New York, NY

$17.50 - $22.75/hr

Modify and refine machine learning data creation, annotation, and rating guidelines. Model Training and Evaluation: * Initiate model training processes using internal tools and command-line ...

Encord

Human Data Operations Strategist

New York, NY · On-site

Oversee data annotation projects, translating complex AI and machine learning requirements into clear workflows and instructions for data annotation teams * Ensure the highest standards of data ...

Encord

Human Data Operations Strategist

New York, NY · On-site

Oversee data annotation projects, translating complex AI and machine learning requirements into clear workflows and instructions for data annotation teams * Ensure the highest standards of data ...

Aquent

Senior AI Data Operations Analyst

Manhattan, NY · On-site +1

$47 - $51/hr

Execute & Champion Data Annotation: Perform hands-on data annotations and lead larger, cross ... Strong functional understanding of machine learning product development and how ML/LLM/agentic ...

TSMG

AI/ML Data Contributor

New York, NY

Previous experience in data annotation, QA, or testing * Interest in AI, machine learning, or emerging technologies What We Offer * Paid, flexible task-based work * Opportunity to work on innovative ...

TSMG

AI/ML Data Contributor

New York, NY · Remote

Previous experience in data annotation, QA, or testing * Interest in AI, machine learning, or emerging technologies What We Offer * Paid, flexible task-based work * Opportunity to work on innovative ...

TSMG

AI/ML Data Contributor

New York, NY

Previous experience in data annotation, QA, or testing * Interest in AI, machine learning, or emerging technologies What We Offer * Paid, flexible task-based work * Opportunity to work on innovative ...

TSMG

AI/ML Data Contributor

New York, NY

Previous experience in data annotation, QA, or testing * Interest in AI, machine learning, or emerging technologies What We Offer * Paid, flexible task-based work * Opportunity to work on innovative ...

TSMG

AI/ML Data Contributor

New York, NY · Remote

Previous experience in data annotation, QA, or testing * Interest in AI, machine learning, or emerging technologies What We Offer * Paid, flexible task-based work * Opportunity to work on innovative ...

TSMG

AI/ML Data Contributor

New York, NY

Previous experience in data annotation, QA, or testing * Interest in AI, machine learning, or emerging technologies What We Offer * Paid, flexible task-based work * Opportunity to work on innovative ...

Teleskope

Jr. AI Engineer - Data Annotation

New York, NY · On-site

$75K - $90K/yr

The work is high-impact and the data is messy; a big part of the job is learning, through the work ... What You'll Do * Do hands-on data annotation and quality control (labeling, reviewing, and ...

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Freelance Machine Learning Data Annotation information

What is the difference between Freelance Machine Learning Data Annotation vs Data Labeler?

AspectFreelance Machine Learning Data AnnotationData Labeler
CredentialsBasic understanding of annotation tools, sometimes with specialized domain knowledgeTypically no formal credentials required
Work EnvironmentRemote, flexible, project-basedOften remote or in-house, depending on employer
Industry UsageUsed in AI/ML development for training datasetsUsed in data preparation for various industries, including AI
Search/Comparison IntentFocuses on freelance opportunities, project scope, and toolsMore general, often employed by companies for data labeling tasks

Freelance Machine Learning Data Annotation involves independently completing annotation tasks for AI models, often with specialized tools and domain knowledge. Data Labelers typically perform similar tasks but may work as employees or contractors within a company. The main difference lies in the freelance nature and project-based work of data annotation roles.

What are the key skills and qualifications needed to thrive as a Freelance Machine Learning Data Annotation specialist, and why are they important?

To thrive as a Freelance Machine Learning Data Annotation specialist, you need attention to detail, basic knowledge of data labeling concepts, and familiarity with machine learning data types. Experience with annotation tools (such as Labelbox, RectLabel, or CVAT) and understanding of data privacy protocols are commonly required. Strong communication, time management, and the ability to follow complex guidelines are essential soft skills for delivering accurate results. These skills ensure high-quality, consistent data annotation, which is critical for effective machine learning model training and performance.

What is freelance machine learning data annotation?

Freelance machine learning data annotation involves labeling or tagging data—such as images, text, audio, or video—to help train machine learning models. As a freelancer, you work independently or through platforms, completing specific annotation tasks assigned by companies or researchers. This work is essential because high-quality labeled data is required for AI systems to learn and make accurate predictions. Annotators may categorize images, transcribe speech, or highlight relevant information in documents. The flexibility of freelancing allows you to choose projects and work remotely.

What are some common challenges faced by freelance machine learning data annotators, and how can they be managed?

Freelance machine learning data annotators often encounter challenges such as maintaining data accuracy, handling repetitive tasks, and understanding complex annotation guidelines. Staying organized and regularly reviewing project instructions can help ensure consistency and quality in annotations. Additionally, communicating proactively with project managers and utilizing annotation tools efficiently can help manage workload and clarify uncertainties. Building expertise in different data types (text, image, audio) also allows annotators to diversify their projects and reduce monotony.
What are the most commonly searched types of Machine Learning Data Annotation jobs in New York? The most popular types of Machine Learning Data Annotation jobs in New York are:
What are popular job titles related to Freelance Machine Learning Data Annotation jobs in New York? For Freelance Machine Learning Data Annotation jobs in New York, the most frequently searched job titles are:
What job categories do people searching Freelance Machine Learning Data Annotation jobs in New York look for? The top searched job categories for Freelance Machine Learning Data Annotation jobs in New York are:
What cities in New York are hiring for Freelance Machine Learning Data Annotation jobs? Cities in New York with the most Freelance Machine Learning Data Annotation job openings:
Freelance Machine Learning Data Annotation jobs near you
Infographic showing various Freelance Machine Learning Data Annotation job openings in New York as of July 2026, with employment types broken down into 19% Full Time, 7% Part Time, 68% Contract, and 6% Nights. Highlights an 22% Physical, and 78% Remote job distribution.

Data Quality Analyst

Welocalize, Inc.

New York, NY • On-site

Full-time

Re-posted 12 days ago

Welocalize rating

6.5

Company rating: 6.5 out of 10

Based on 13 frontline employees who took The Breakroom Quiz

327th of 481 rated business services

Job description

If you have a Candidate Login already, but have forgotten your password please use the steps to reset your password. If you have forgotten your email login, please contact servicedesk@welocalize.com subject Workday Candidate Login

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Job Responsibilities:

The ideal candidate will have a foundational understanding of machine learning, data annotation, quality assurance, and natural language processing. They will play a pivotal role in updating our machine learning models and ensuring their efficacy.

MAIN TASKS & RESPONSIBILITIES

Machine Learning Model Updates:

  • Update training and test model databases with new or amended synthetic textual and image data.
  • Modify and refine machine learning data creation, annotation, and rating guidelines.

Model Training and Evaluation:

  • Initiate model training processes using internal tools and command-line interfaces.
  • Evaluate the performance of trained models to gauge their efficacy and readiness for deployment.

Data Management and Annotation:

  • Design and develop test and training datasets as per the criteria provided by the project manager and other full-time employees.
  • Handle data efficiently, ensuring its integrity throughout the workflow.
  • Engage in data relevance tasks, ensuring data sets are aligned with project goals.
  • Annotate data accurately, ensuring it adheres to set guidelines.

Quality Assurance and Analysis:

  • Conduct manual quality analysis of model results.
  • Recognize error patterns and report anomalies for further investigation.
  • Deliver detailed reports on findings, including aspects such as utterance quality, LLM evaluation, ASR bug tracking, and customer pain points to be reviewed by the User Experience Research team.
  • Implement basic quality control measures and ensure the reliability of processed data.
  • Utilize intermediate data analysis techniques to extract insights and inform decision-making.
  • Arbitrate discrepancies effectively, ensuring consistent data quality.

Linguistic and NLP Tasks:

  • Apply basic knowledge of natural language processing and linguistics to data processing tasks.
  • Ensure linguistic accuracy in all processed and annotated data.

REQUIREMENTS

Preferred Qualifications:

  • Bachelor's degree in Computer Science, Data Science, Linguistics or Computational Linguistics or a related field.

Experience:

  • Ability to work in a fast-paced, collaborative environment.
  • Excellent communication skills

Skills & Knowledge:

  • Familiarity with command-line tools and interfaces.
  • Strong analytical skills with the ability to identify patterns and anomalies.

Additional Information:

This role primarily focuses on English US data sets; however, familiarity with translation or multi-lingual data sets can be a plus for future projects.

Additional Job Details:

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