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Data Annotation Research Jobs (NOW HIRING)

Mercor

AI Research Collaborator - PhD

New York, NY · Remote

$80 - $110/hr

Past experience in AI training , model evaluation, and data annotation. Resources & Support * For details about the interview process and platform information, please check: * For any help or support ...

Mercor

Research Scientist | Upto $100/hr

New York, NY · Remote

$100/hr

Guide research teams to close knowledge gaps in STEM domains by surfacing edge cases, ambiguities ... Prior experience with data annotation, labeling, evaluation, or human feedback collection.

Alignerr

Python Software Engineer - AI Workflows

Collaborate with data, research, and engineering teams to support model training and evaluation ... Prior experience with data annotation, data quality, or evaluation systems * Familiarity with AI/ML ...

Alignerr

Python Software Engineer - AI Workflows

Collaborate with data, research, and engineering teams to support model training and evaluation ... Prior experience with data annotation, data quality, or evaluation systems * Familiarity with AI/ML ...

Mercor

Data Scientist | Upto $100/hr

New York, NY · Remote

$100/hr

Guide research and engineering teams to close knowledge gaps in AI and data science domains ... Prior experience with data annotation, labeling, evaluation, or human feedback collection.

Mercor

Data Science Expert - Fully Remote

New York, NY · Remote

$70 - $100/hr

Guide research and engineering teams to close knowledge gaps in AI and data science domains ... Prior experience with data annotation, labeling, evaluation, or human feedback collection.

Pumpkin Intelligence, Inc.

Data Labeler

$30K - $50K/yr

... researchers and engineers * Help improve evaluation guidelines and annotation processes ... Can make consistent decisions across large volumes of data * Enjoys analyzing nuanced situations ...

Abaka AI

Research Program Associate

Mountain View, CA · On-site

As a Research Program Associate, you will support the operational coordination and execution of ... collection, data cleaning, data annotation, and OTS datasets. Founded in 2021, the company is ...

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All JobsData Annotation Research Jobs

Data Annotation Research information

What qualifications do I need for data annotation?

Data annotation research roles typically require basic computer skills, attention to detail, and familiarity with annotation tools or platforms. A high school diploma or equivalent is usually sufficient, though some positions may prefer experience with data labeling, machine learning concepts, or specific software. Strong communication skills and the ability to work independently are also beneficial.

What are some common challenges faced in Data Annotation Research roles, and how can they be addressed?

Professionals in Data Annotation Research often encounter challenges such as maintaining consistency in labeling, dealing with ambiguous data, and managing large datasets efficiently. These issues can be addressed by following detailed annotation guidelines, participating in regular calibration sessions with the team, and utilizing annotation tools that support quality control checks. Collaboration with data scientists and project managers is essential to clarify ambiguities and ensure that annotated data meets the project's requirements. Staying proactive in communication and continuous learning helps to minimize errors and improve overall data quality.

Does data annotation actually pay?

Data annotation research jobs typically pay hourly or per task rates, with wages ranging from minimum wage to higher rates depending on experience and complexity of the work. Many positions are freelance or remote, requiring basic skills in data labeling tools and attention to detail. Payment is generally reliable, but rates vary by employer and project.

How hard is it to get hired by data annotation?

Getting hired for a data annotation research role typically requires basic computer skills, attention to detail, and sometimes familiarity with annotation tools or platforms. Many positions are entry-level and do not require advanced education, making the hiring process relatively accessible for those with the right skills and reliability.

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

AspectData Annotation ResearchData Labeling Specialist
CredentialsTypically requires a background in data science, research methods, or related fieldsOften requires basic technical skills and experience with labeling tools
Work EnvironmentResearch labs, tech companies, or remote research teamsData centers, tech companies, or remote labeling teams
Industry UsageUsed in AI/ML research, developing annotation methodologiesUsed in preparing datasets for machine learning models
Search & Comparison IntentUnderstanding research-focused roles in data annotationLooking for practical data labeling jobs

Data Annotation Research involves exploring new annotation techniques and improving data quality for AI models, often requiring research skills. In contrast, Data Labeling Specialists focus on applying existing labeling tools to annotate datasets efficiently. Both roles are essential in AI development but differ in scope and expertise.

Is data annotation real or fake?

Data annotation is a real and essential process in machine learning and AI development, involving labeling data such as images, text, or audio to train algorithms. Data annotation jobs require attention to detail and often use tools like labeling platforms or software, making them a legitimate employment opportunity in the tech industry.

What is data annotation research?

Data annotation research involves studying and developing methods for labeling data, such as images, text, or audio, to be used in training machine learning models. Researchers in this field focus on improving annotation accuracy, efficiency, and scalability, as well as addressing challenges like bias and consistency. This work is critical because high-quality annotated data is essential for building effective AI systems. Data annotation research often includes exploring new tools, techniques, and guidelines for human annotators or automated labeling systems.

What are the key skills and qualifications needed to thrive as a Data Annotation Researcher, and why are they important?

To thrive as a Data Annotation Researcher, you need strong attention to detail, analytical thinking, and familiarity with data labeling concepts, often supported by a degree in computer science, linguistics, or a related field. Experience with annotation platforms, data management tools, and sometimes knowledge of programming languages like Python are typically required. Excellent communication, problem-solving abilities, and the capacity to work independently set standout contributors apart. These skills ensure high-quality, accurate data labeling, which is crucial for developing reliable AI and machine learning models.
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Data Annotation Research jobs near you
Infographic showing various Data Annotation Research job openings in the United States as of June 2026, with employment types broken down into 4% As Needed, 3% Full Time, 71% Part Time, 3% Temporary, 17% Contract, and 2% Nights. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.
AI Research Collaborator - PhD

AI Research Collaborator - PhD

Mercor

New York, NY • Remote

$80 - $110/hr

Full-time

Posted 7 days ago

Job description

About the job

Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey.

Position: Academic Research Collaborator - Professors & PhDs
Type: Contract
Compensation: $80–$110/hour
Location: Remote

Role Responsibilities

  • Design challenging, real-world domain-specific problems in areas like financial modeling, legal reasoning, econometrics, ML, and coding. Focus on addressing core capability loss failures in frontier AI models.
  • Integrate problems into an Agentic development environment using Python. Prepare all necessary components for robust task execution.
  • Evaluate the target model's performance on designed tasks. Analyze outcomes to improve model reasoning and outputs.
  • Identify tasks where the model fails to pass tests. Classify failures as logical reasoning issues to guide future improvements.
  • Collaborate with domain experts to enhance AI model training and ensure task relevance and accuracy.

Qualifications

Must-Have

  • Current or retired professor, or PhD student, in STEM or professional/quantitative domains.
  • Degree or PhD in progress from a top university.
  • Working proficiency in Python applied in research, industry, GitHub, or coursework.
  • Ability to engage reliably for 30+ hours/week during weekdays.
  • Basic ability to work independently and manage time effectively.
  • Strong verbal and written communication skills.

Preferred

  • Past experience in AI training, model evaluation, and data annotation.

Resources & Support

  • For details about the interview process and platform information, please check: https://talent.docs.mercor.com/welcome
  • For any help or support, reach out to: support@mercor.com

PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.