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Annotation Labelling Jobs in New York (NOW HIRING)

Delivery Lead

New York, NY · Remote

$110K - $140K/yr

... annotation to delivery. We design and create datasets from scratch, recruit and manage the domain experts who evaluate model output, and run everything through our own platform, Label Studio, the ...

ML Engineer

New York, NY · On-site +1

$170K - $185K/yr

Building automated annotation pipelines that use SAM and vision-language models to pre-label datasets, cutting model iteration cycles by 5-10x * Creating model performance dashboards that surface ...

Built a labeling rubric, ontology, or ground‑truth spec that a large annotation org executed against in production. * Worked directly with research scientists at frontier AI labs or autonomy ...

Human Data Architect, Quality

Manhattan, NY · On-site

$70.25 - $90.50/hr

Built a labeling rubric, ontology, or ground‑truth spec that a large annotation org executed against in production. * Worked directly with research scientists at frontier AI labs or autonomy ...

Generate, label, and curate high-quality training and evaluation datasets based on real-world ... Prior experience with data annotation, model evaluation, or quality assurance for AI systems.

Research Engineers, Data

New York, NY · On-site

$150K - $250K/yr

Develop synthetic data, annotation, and feedback-loop strategies to improve system performance in ... You have built data pipelines, evaluation datasets, labeling workflows, retrieval corpora, or ...

Showing results 41-60

Annotation Labelling information

What is annotation labelling?

Annotation labelling is the process of tagging or marking data—such as images, text, or audio—with relevant information or labels. This is an essential step in preparing datasets for machine learning and artificial intelligence models, as it helps algorithms understand and learn from raw data. Annotation labelling can include tasks like identifying objects in photos, transcribing speech, or categorizing text. Skilled annotators ensure accuracy and consistency to improve model performance. People in this role often use specialized tools or software to streamline and standardize the annotation process.

What are the key skills and qualifications needed to thrive as an annotation labelling specialist?

To thrive as an Annotation Labelling Specialist, you need strong attention to detail, data analysis capabilities, and familiarity with data annotation standards, usually supported by a background in computer science or related fields. Proficiency with annotation tools such as Labelbox, CVAT, or Supervisely, and sometimes knowledge of basic programming or scripting, is typically required. Excellent communication, consistency, and the ability to follow complex instructions are crucial soft skills for producing high-quality labeled data. These skills ensure the accuracy and reliability of datasets, which are foundational for successful machine learning and AI model development.

What are some common challenges faced by annotation labelling professionals, and how can they be managed?

Annotation Labelling professionals often encounter challenges such as maintaining high accuracy while handling repetitive data, meeting tight deadlines, and adapting to evolving project guidelines. To manage these, it’s important to develop strong attention to detail, regularly communicate with team leads to clarify instructions, and leverage annotation tools efficiently. Collaborating closely with quality assurance teams can also help identify and correct errors early, ensuring consistently high-quality outputs.

What is the difference between Annotation Labelling vs Data Labeling Specialist?

AspectAnnotation LabellingData Labeling Specialist
CredentialsBasic technical skills, attention to detailSimilar skills, sometimes additional domain knowledge
Work EnvironmentData annotation platforms, remote or officeData annotation tasks, often remote or in-office
Industry UsageAI, machine learning, autonomous vehiclesAI, machine learning, healthcare, retail
Search & ComparisonCommonly compared for entry-level data tasksRelated but broader role

Annotation Labelling involves marking data such as images, text, or videos to train AI models. Data Labeling Specialists perform similar tasks but may have a broader scope, including verifying and managing labeled data. Both roles are essential in AI development, often overlapping in skills and work environment, but Annotation Labelling is more focused on the annotation process itself.

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

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

What cities in New York are hiring for Annotation Labelling jobs?

Cities in New York with the most Annotation Labelling job openings:

Media & Information AI Training Specialist -- Task Creation & Model Evaluation

Manhattan, NY • On-site

BAM Ventures
Investment Clubs and Venture Capital Companies • 1 - 10 employees

Other

Posted 9 days ago


Job description

About Rise Data Labs

Rise Data Labs is a leading AI training and data annotation company that specializes in creating high-quality training data for artificial intelligence systems. We work with top AI companies and research institutions to improve machine learning models through expert human annotation and validation. Our team of domain specialists, subject matter experts, and quality assurance professionals work across various fields including journalism, editorial, and video/film production. We pride ourselves on our attention to detail, domain expertise, and commitment to delivering accurate, high-quality training data.

Job Overview

As a Media & Information AI Training Specialist at Rise Data Labs, you will play a crucial role in training and enhancing AI models specifically tailored for journalism, editorial, and video/film production work. This role goes beyond traditional annotation and labeling — you'll author realistic, economically valuable media tasks and rubrics based on your own professional experience, then grade AI-generated deliverables against them.

What You'll Do
  • Create realistic work scenarios based on your own professional experience — e.g., drafting or editing an article, fact-checking and sourcing, writing a script or shot list, reviewing a rough cut or storyboard
  • Supply the kinds of reference materials you'd normally work from (source documents, style guides, scripts, production notes)
  • Write detailed rubrics specifying exactly what a correct, publication‑ready or production‑ready deliverable requires — accurate sourcing, correct style/format, sound editorial or production judgment
  • Grade AI-generated deliverables (often written pieces, scripts, or production documents) against your rubric
  • Join calibration sessions with other experts to ensure consistent scoring across the benchmark
Preferred Qualifications
  • Prior hands‑on experience as a Journalist, Editor, Writer, Producer, Director, or Video Editor
  • Comfort reviewing detailed written or production work product against professional standards
  • Prior experience with AI model training, evaluation, or benchmark development is a plus
What We Offer

At Rise Data Labs, we value our contributors and strive to create a supportive, flexible working environment. We offer opportunities for professional development in the AI field and the chance to work on innovative projects that directly shape the future of AI in media, journalism, and video production.

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BAM Ventures logo

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