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Data Annotation For Ai Jobs in New York (NOW HIRING)

TSMG

AI/ML Data Contributor

New York, NY

Perform AI/ML-related tasks such as data labeling, annotation, and content evaluation * Participate ... Potential for ongoing project participation We may use artificial intelligence (AI) tools to ...

TSMG

AI/ML Data Contributor

New York, NY · Remote

Perform AI/ML-related tasks such as data labeling, annotation, and content evaluation * Participate ... Potential for ongoing project participation We may use artificial intelligence (AI) tools to ...

TSMG

AI/ML Data Contributor

New York, NY

Perform AI/ML-related tasks such as data labeling, annotation, and content evaluation * Participate ... Potential for ongoing project participation We may use artificial intelligence (AI) tools to ...

TSMG

AI/ML Data Contributor

New York, NY

Perform AI/ML-related tasks such as data labeling, annotation, and content evaluation * Participate ... Potential for ongoing project participation We may use artificial intelligence (AI) tools to ...

TSMG

AI/ML Data Contributor

New York, NY · Remote

Perform AI/ML-related tasks such as data labeling, annotation, and content evaluation * Participate ... Potential for ongoing project participation We may use artificial intelligence (AI) tools to ...

TSMG

AI/ML Data Contributor

New York, NY

Perform AI/ML-related tasks such as data labeling, annotation, and content evaluation * Participate ... Potential for ongoing project participation We may use artificial intelligence (AI) tools to ...

YO AI Labs

AI Finance Expert - Remote

New York, NY · Remote

$93K - $116K/yr

Analyze, review, and edit AI-generated financial content for accuracy, clarity, and relevance ... Data Annotation * Problem-Solving * Independent Research * Attention to Detail Preferred ...

Distyl AI

Research Engineers, Data

New York, NY · On-site

$150K - $250K/yr

This role is for engineers who are excited to investigate how AI systems should be designed ... Develop synthetic data, annotation, and feedback-loop strategies to improve system performance in ...

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Data Annotation For Ai information

What is data annotation for AI?

Data annotation for AI is the process of labeling or tagging data—such as text, images, audio, or video—to make it understandable for machine learning models. Annotators add relevant information to raw data, helping AI systems learn to recognize patterns and make accurate predictions. This step is crucial for training, validating, and testing AI algorithms, especially in tasks like computer vision and natural language processing. High-quality data annotation directly impacts the effectiveness and reliability of AI applications.

What are some common challenges faced by data annotators working on AI projects, and how can they be addressed?

Data annotators for AI often encounter challenges such as maintaining consistency across large datasets, understanding ambiguous labeling instructions, and managing repetitive tasks. To address these issues, it's important to actively seek clarification on guidelines, participate in team discussions to align on labeling standards, and use annotation tools that flag inconsistencies. Regular feedback sessions with project leads also help improve accuracy and efficiency, fostering a collaborative and supportive work environment.

What are the key skills and qualifications needed to thrive as a data annotation specialist for AI, and why are they important?

To thrive as a Data Annotation Specialist for AI, you need a keen eye for detail, a solid understanding of data labeling concepts, and often a background in the relevant domain (such as language, images, or audio). Proficiency with annotation platforms, data management systems, and basic familiarity with tools like Excel or Python can be highly valuable. Strong communication, consistency, and time management skills help ensure accuracy and meet project deadlines. These abilities are crucial because high-quality, well-annotated data is foundational for training reliable and effective AI models.

What is the difference between Data Annotation For Ai vs Data Labeler?

AspectData Annotation For AiData Labeler
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentRemote or on-site, tech companies, AI projectsRemote or on-site, data processing companies
Industry UsageArtificial Intelligence, Machine LearningData management, content moderation
Job FocusPreparing data for AI algorithms through annotationLabeling data for various purposes, including AI

Data Annotation For Ai involves preparing datasets specifically for training AI models, focusing on detailed annotations. Data Labeler is a broader role that includes labeling data for multiple purposes, including AI but also other data management tasks. While both roles require similar skills, Data Annotation For Ai is more specialized towards AI development projects.

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Data Annotation For Ai jobs near you
Infographic showing various Data Annotation For Ai job openings in New York as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 13% Part Time, and 3% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution.

AI Training Specialist - Organic & Inorganic Chemistry Expert

BAM Ventures

Manhattan, NY • On-site

$70 - $90/hr

Other

Posted 3 days ago

New

Job description

Job Overview

As an AI Training Specialist with expertise in organic and inorganic chemistry, you will play a crucial role in enhancing the performance of our AI models. Your responsibilities will include training AI systems through data annotation and labeling, reviewing AI-generated content for accuracy, and providing your domain expertise to ensure high-quality data for machine learning applications.

Key Responsibilities
  • Train and improve AI models by annotating and labeling data specific to organic and inorganic chemistry.
  • Review and validate AI-generated content for accuracy and relevance.
  • Provide domain-specific knowledge to enhance AI model performance and reliability.
  • Work on various AI training projects across different fields, ensuring data quality and consistency.
  • Collaborate with cross-functional teams to deliver high-quality outcomes in AI training initiatives.
Required Skills and Qualifications
  • Bachelor's degree in Chemistry or a related field.
  • Strong understanding of organic and inorganic chemistry concepts.
  • Experience in data annotation or AI training roles.
  • Attention to detail and commitment to quality assurance.
  • Familiarity with machine learning principles and AI technologies.
Preferred Qualifications
  • Advanced degree in Chemistry or related fields.
  • Experience with AI tools and software for data annotation.
  • Strong analytical and problem-solving skills.
  • Excellent communication and collaboration abilities.
What We Offer

At Rise Data Labs, we provide a dynamic work environment that fosters innovation and professional growth. Our team enjoys competitive compensation, flexible working hours, and opportunities for continuous learning in the rapidly evolving field of AI.

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About BAM Ventures

Sourced by ZipRecruiter

Industry

Investment clubs and venture capital companies

Company size

1 - 10 Employees

Headquarters location

Santa Monica, CA, US

Year founded

2014

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