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Data Annotation Tech Jobs in Maryland (NOW HIRING)

Axle

Data Scientist II

Rockville, MD

(ID: 2026-2574) Axle is a bioscience and information technology company that offers advancements in ... annotation, DEG), and Digital Spatial Profiling (annotation, QC, normalization, spatial ...

Axle

Data Scientist II

Rockville, MD · On-site

(ID: 2026-2574) Axle is a bioscience and information technology company that offers advancements in ... annotation, DEG), and Digital Spatial Profiling (annotation, QC, normalization, spatial ...

Axle

Data Scientist II

Rockville, MD

(ID: 2026-2574) Axle is a bioscience and information technology company that offers advancements in ... annotation, DEG), and Digital Spatial Profiling (annotation, QC, normalization, spatial ...

BCC - LH

Subject Matter Expert- RxNav

Bethesda, MD · On-site

Department of Health and Human Services (DHHS) agencies to develop data science solutions to ... Experience in content development and/or text annotation (e.g., annotation of certain types of ...

BCC - LH

Subject Matter Expert- RxNav

Bethesda, MD

Department of Health and Human Services (DHHS) agencies to develop data science solutions to ... Experience in content development and/or text annotation (e.g., annotation of certain types of ...

Axle

Data Science Fellow - AI/NLP

Rockville, MD

(ID: 2026-2316) Axle is a bioscience and information technology company that offers advancements in ... Develop benchmark datasets, annotation guidelines, and evaluation pipelines for scientific ...

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All JobsData Annotation Tech JobsData Annotation Tech Jobs in Maryland

Data Annotation Tech information

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$11

$22

$33

How much do data annotation tech jobs pay per hour?

As of Jun 28, 2026, the average hourly pay for data annotation tech in Maryland is $22.17, according to ZipRecruiter salary data. Most workers in this role earn between $16.35 and $26.35 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Data Annotation Tech position, and why are they important?

To thrive as a Data Annotation Tech, you need keen attention to detail, basic computer literacy, and familiarity with data labeling standards, often supported by a high school diploma or equivalent. Experience with annotation platforms, image or text labeling tools, and basic knowledge of data management systems is highly valuable. Strong organizational skills, patience, and effective communication set top candidates apart in this field. These skills and qualities ensure annotated data is accurate, consistent, and valuable for machine learning or AI projects.

What does a typical day look like for a Data Annotation Tech?

A typical day as a Data Annotation Tech involves reviewing large sets of data—such as images, text, or audio—and accurately labeling or categorizing them using specialized software. You may work independently or as part of a team, following specific project guidelines to ensure data integrity and consistency. Collaboration with project managers or data scientists is common when clarifying ambiguous data points or addressing annotation challenges. Additionally, productivity targets and quality checks are a regular part of the workflow, helping to keep projects on schedule and maintain high standards.

Is data annotation real or fake?

Data annotation is a legitimate job involving labeling data such as images, text, or audio to train machine learning models. It requires attention to detail and familiarity with annotation tools, and it is widely used in AI development. The work is real and essential for creating accurate AI systems.

Is data annotation tech still hiring?

Data annotation technician roles are currently in demand as companies expand their AI and machine learning projects. These positions often require attention to detail, familiarity with annotation tools, and sometimes basic knowledge of data privacy standards. Job availability can vary by industry and region but generally remains steady due to ongoing AI development needs.

How much does data annotation tech pay?

Data annotation technicians typically earn between $12 and $20 per hour, depending on experience, location, and the complexity of the annotation tasks. Entry-level roles may pay closer to minimum wage, while experienced workers or those with specialized skills can earn higher wages. Some positions offer freelance or remote work with flexible pay rates.

Does data annotation really pay you?

Data annotation jobs typically pay hourly or per task, with rates varying based on the platform, complexity of the work, and experience. Many companies and platforms offer remote work opportunities, and pay can range from minimum wage to higher rates for specialized skills or faster completion times.

What is a Data Annotation Tech job?

A Data Annotation Tech is responsible for labeling and categorizing data, such as text, images, audio, or video, to train machine learning models. They follow specific guidelines to ensure accuracy and consistency in annotations, which helps improve the performance of AI systems. This role often involves repetitive tasks, attention to detail, and familiarity with various annotation tools. Data annotation is crucial for AI development in industries like healthcare, finance, and autonomous driving.

What are the most commonly searched types of Data Annotation Tech jobs in Maryland? The most popular types of Data Annotation Tech jobs in Maryland are:
What are popular job titles related to Data Annotation Tech jobs in Maryland? For Data Annotation Tech jobs in Maryland, the most frequently searched job titles are:
What job categories do people searching Data Annotation Tech jobs in Maryland look for? The top searched job categories for Data Annotation Tech jobs in Maryland are:
What cities in Maryland are hiring for Data Annotation Tech jobs? Cities in Maryland with the most Data Annotation Tech job openings:
Data Annotation Tech jobs near you
Infographic showing various Data Annotation Tech job openings in Maryland as of June 2026, with employment types broken down into 3% As Needed, 55% Full Time, 16% Part Time, 3% Temporary, and 23% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $46,113 per year, or $22.2 per hour.
Assistant Research Scientist (PREP0004176)

Assistant Research Scientist (PREP0004176)

Johns Hopkins University

Gaithersburg, MD • On-site

Full-time

Posted 21 days ago

Johns Hopkins Medicine rating

7.5

Company rating: 7.5 out of 10

Based on 202 frontline employees who took The Breakroom Quiz

228th of 877 rated healthcare providers

Job description

Description
PREP Research Associate
This position is part of the National Institute of Standards and Technology (NIST) Professional Research Experience Program (PREP). NIST recognizes that its research staff may want to collaborate with researchers at academic institutions on specific projects of mutual interest and, therefore, requires those institutions to be recipients of a PREP award. The PREP program involves staff from a wide range of backgrounds conducting scientific research across various fields. Individuals in this position will perform technical work supporting the collaboration's scientific research.
Research Title:
Reliability of Human and LLM Annotations for AI Risk Assessment
The work will entail:
This project focuses on using Large Language Models (LLMs) to provide annotations of evaluation data (a.k.a., LLM as judge), and the design of an Inter-Annotator Agreement study to assess the reliability of both human and LLM annotations. The candidate will explore assessing the indicators of a given AI-related risk, determining how to identify them, and providing annotators with examples to annotate the presence of various risks. The project aims to develop an annotation framework for AI risk assessment and establish metrics for data quality in AI risk research, supporting broader work at NIST in assessing and measuring the validity and reliability of AI-related risks in data annotation.
U.S. Citizen Preferred
Key responsibilities will include but are not limited to:
  • Gain familiarity with existing literature on data annotation and LLM as judge
  • Understand NIST's role and ongoing efforts in assessing and measuring the validity and reliability of AI-related risks in data annotation
  • Contribute to developing an annotation framework for AI risk assessment
  • Collaborate effectively with cross-functional and interdisciplinary stakeholders to ensure successful project outcomes

Deliverables
  • Contributions to a NIST report that supports ongoing NIST AI evaluation efforts focused on the design of an Inter-Annotator Agreement to assess the reliability of both human and LLM annotations.

Qualifications
  • Background in Computer Science, Data Science, or related field.
  • Education level: Bachelor's or Graduate Degree
  • Strong interest in data annotation and AI risks
  • Familiarity with scientific reading and technical writing

Application Instructions
Please upload the following with your application:
• CV/Resume
*Please limit C.V to 3 pages only and ONLY include a valid email address for your contact info. Your resume will not be considered if the following information is included on your CV/resume.
• Self portraits
• Phone number
• Home address/Country
• Citizenship status
• Languages spoken
• Sex/Gender
Privacy Act Statement
Authority: 15 U.S.C. § 278g-1(e)(1) and (e)(3) and 15 U.S.C. § 272(b) and (c)
Purpose: The National Institute for Standards and Technology (NIST) hosts the Professional Research Experience Program (PREP) which is designed to provide valuable laboratory experience and financial assistance to undergraduates, post-bachelor's degree holders, graduate students, master's degree holders, postdocs, and faculty.
PREP is a 5-year cooperative agreement between NIST laboratories and participating PREP Universities to establish a collaborative research relationship between NIST and U.S. institutions of higher education in the following disciplines including (but may not be limited to) biochemistry, biological sciences, chemistry, computer science, engineering, electronics, materials science, mathematics, nanoscale science, neutron science, physical science, physics, and statistics. This collection of information is needed to facilitate administrative functions of the PREP Program.
Routine Uses: NIST will use the information collected to perform the requisite reviews of the applications to determine eligibility, and to meet programmatic requirements. Disclosure of this information is also subject to all the published routine uses as identified in the Privacy Act System of Records Notices: NIST-1: NIST Associates.
Disclosure: Furnishing this information is voluntary. When you submit the form, you are indicating your voluntary consent for NIST to use of the information you submit for the purpose stated.

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