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Freelance Machine Learning Data Annotation Jobs in New York

Mercor

AI Researcher

New York, NY · Remote

$70 - $100/hr

... experience in Machine Learning , Data Science , Software Engineering , Computer Science ... Prior experience with data annotation, labeling, evaluation, or human feedback collection.

Mercor

AI Research Scientist - GenAI

New York, NY · Remote

$70 - $100/hr

... experience in Machine Learning , Data Science , Software Engineering , Computer Science ... Prior experience with data annotation, labeling, evaluation, or human feedback collection.

Mercor

Data Scientist

New York, NY · Remote

$70 - $100/hr

... applied machine learning . * Ability to commit to 40 hours per week during weekdays for the ... Prior experience with data annotation , labeling, evaluation, or human feedback collection.

Mercor

Data Science Manager

New York, NY · Remote

$70 - $100/hr

... applied machine learning . * Ability to commit to 40 hours per week during weekdays for the ... Prior experience with data annotation , labeling, evaluation, or human feedback collection.

Mercor

Data Scientist - AI/ML Expert

New York, NY · Remote

$70 - $100/hr

... applied machine learning . * Ability to commit to 40 hours per week during weekdays for the ... Prior experience with data annotation , labeling, evaluation, or human feedback collection.

Microsoft AI

Machine Learning

Manhattan, NY · On-site

... fixing data quality and curation, working with collaborators on creating new products). • OR Master's Degree in Computer Science, Machine Learning, or related field AND 5+ years experience (e.g ...

Mercor

Lead Data Scientist | Upto $100/hr

New York, NY · Remote

$100/hr

... applied machine learning . * Ability to commit to 40 hours per week during weekdays for the ... Prior experience with data annotation , labeling, evaluation, or human feedback collection.

SysMind Tech

Machine Learning

Manhattan, NY · On-site

$85/hr

Stay updated with the latest trends and technologies in data science and machine learning. Basic Qualifications: Proficient in Python, Pandas, NumPy, Scikit-Learn, PySpark Bachelor s degree in ...

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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:
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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 June 2026, with employment types broken down into 33% Internship, 33% Full Time, and 34% Contract. Highlights an 67% In-person, and 33% Remote job distribution.

Machine Learning Engineer

Seven Seven Software

Newark, NJ • On-site

Full-time

Posted 7 days ago

Job description

• Strong computer science fundamentals such as algorithms, data structures, multithreading, object-oriented development, distributed applications, client-server architecture.
• Design and implement Machine learning models and data ingestion pipelines.
• Develop and support a platform that enables data scientists to rapidly develop, train, and experiment with machine learning models.
• Expand and optimize data pipelines, data flow, and collection for cross functional teams.
• Create and maintain optimal data pipeline architecture by assembling large, complex data sets to meet functional and non-functional business requirements.
• Identify and implement internal process improvements including automating manual processes, optimizing data delivery, and redesigning infrastructure for greater scalability.
• Support the building of machine learning, data platforms, and infrastructure required for optimal data extraction, transformations, and loading of data from a wide variety of data sources.
• Work with architecture, data, and design teams to assist with data related technical issues and support data infrastructure needs.
• Implement Machine Learning (ML) and Big Data platforms in Hybrid and multi-cloud environment specifically in AWS SageMaker environment
• Experience in container, streaming and messaging technologies is a plus
• Advanced proficiency with Python framework, Java and Scala
• Extensive knowledge of ML frameworks, libraries, data structures, data modeling, and software architecture.
• Good understanding of mathematics, statistics, and algorithms.
• Excellent analytical and problem-solving abilities.
• Great communication and collaboration skills.
Job Requirements

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