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Monday Through Friday Data Annotation Tech Jobs in Frederick, MD

Bridged Technology LLC

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Audio/Video & Low Voltage Field Technician

Hagerstown, MD · On-site

$19 - $25/hr

Work is scheduled Monday through Friday with an occasional need for Saturday. Company Description Bridged Technology is a leading provider of commercial and government technology solutions across ...

Bridged Technology LLC

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Audio/Video & Low Voltage Field Technician

Hagerstown, MD · On-site

$19 - $25/hr

Work is scheduled Monday through Friday with an occasional need for Saturday. Company Description Bridged Technology is a leading provider of commercial and government technology solutions across ...

Azaaki Solutions

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Biomanufacturing Associate

Rockville, MD · On-site

$31.50/hr

... min unpaid lunch Monday through Friday OT and weekend work may become required there is a ... Ensure data integrity - accurately document and review work prior to submission. * Document, record ...

Shepherd University

Rambassador

Shepherdstown, WV · On-site

$12/hr

Rambassadors lead weekday campus tours held Monday through Friday at 10 a.m. and 2 p.m., and their presence is also required at major admissions events such as Open Houses and Accepted Student Days.

Busy Service Inc

Office Assistant

Laytonsville, MD · Remote

$25 - $30/hr

Office assistant needed Monday through Friday, 8-5 pm. Must have QB's Online experience. Will be assisting Office Admin with some accounting, answering phones, and assisting estimator with setting up ...

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All JobsMonday Through Friday Data Annotation Tech JobsMonday Through Friday Data Annotation Tech Jobs in Frederick, MD

Monday Through Friday Data Annotation Tech information

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$12

$22

$34

How much do monday through friday data annotation tech jobs pay per hour?

As of Aug 27, 2026, the average hourly pay for monday through friday data annotation tech in Frederick, MD is $22.71, according to ZipRecruiter salary data. Most workers in this role earn between $16.73 and $27.02 per hour, depending on experience, location, and employer.

What is a Monday Through Friday Data Annotation Tech?

A Monday Through Friday Data Annotation Tech is a professional responsible for labeling, tagging, or categorizing data—such as text, images, audio, or video—during regular weekday business hours. This role is crucial for training and improving machine learning and artificial intelligence models, as annotated data helps algorithms learn to recognize patterns accurately. Data annotation techs typically use specialized software to ensure data is labeled correctly and consistently according to project guidelines. Working Monday through Friday often means a standard workweek schedule, providing predictable hours and work-life balance.

What does a Monday Through Friday Data Annotation Tech do?

As a Monday Through Friday Data Annotation Tech, you can expect a structured workweek focused on labeling and categorizing large datasets, often using specialized software tools. Your daily responsibilities may include reviewing data for accuracy, following detailed annotation guidelines, and meeting productivity targets. Collaboration is common—techs often communicate with project managers, quality assurance teams, and sometimes developers to clarify requirements or resolve ambiguities in the data. Regular check-ins and feedback sessions help ensure consistency and address any challenges that arise, making teamwork and strong communication skills essential for success in this role.

What skills and qualifications are needed to thrive as a Monday Through Friday Data Annotation Tech?

To thrive as a Data Annotation Tech, you need strong attention to detail, accuracy, and basic computer proficiency, typically supported by a high school diploma or equivalent. Familiarity with data labeling platforms, annotation tools, and sometimes spreadsheet software is commonly required. Strong organizational skills, time management, and the ability to work independently or as part of a remote team are valuable soft skills. These abilities ensure precise data preparation, which is crucial for training high-quality machine learning models.

What is the difference between Monday Through Friday Data Annotation Tech vs Data Labeling Specialist?

AspectMonday Through Friday Data Annotation TechData Labeling Specialist
CredentialsBasic computer skills, training in annotation toolsSimilar credentials, often with training in labeling software
Work EnvironmentOffice or remote, consistent weekday scheduleOffice or remote, similar schedule
Industry UsageCommon in AI/ML companies, tech firmsUsed in AI, autonomous vehicles, healthcare
Job FocusAnnotating data for machine learning modelsLabeling data to train AI systems

Both roles involve data annotation and labeling, often with similar credentials and work environments. The main difference lies in terminology; 'Data Labeling Specialist' is a broader term used across industries, while 'Data Annotation Tech' emphasizes the technical aspect of annotation tools. Both roles typically follow a Monday through Friday schedule and are essential in AI development.

Is Monday Through Friday Data Annotation Tech still hiring?

The availability of Monday Through Friday Data Annotation Tech positions depends on the employer and current job market conditions. These roles are often posted on job boards and may require familiarity with annotation tools and attention to detail. Candidates should check specific company listings for the most up-to-date hiring status.

What are popular job titles related to Monday Through Friday Data Annotation Tech jobs in Frederick, MD?

For Monday Through Friday Data Annotation Tech jobs in Frederick, MD, the most frequently searched job titles are:

Monday Through Friday Data Annotation Tech jobs near you
Infographic showing various Monday Through Friday Data Annotation Tech job openings in Frederick, MD as of August 2026, with employment types broken down into 100% Full Time. Highlights an 67% In-person, and 33% Hybrid job distribution, with an average salary of $47,240 per year, or $22.7 per hour.

Assistant Research Scientist (PREP0004176)

Gaithersburg, MD • On-site

Johns Hopkins University
Colleges, Universities, and Professional Schools • 10K+ employees

8.0

Company rating: 8.0 out of 10

Based on 71 frontline employees who took The Breakroom Quiz

190th of 623 rated colleges and universities

People enjoy working here

Good employer

Recommended by students

Learn more about Johns Hopkins Universityexternal

Full-time

Re-posted 20 days ago

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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About Johns Hopkins University

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Gilman believed that teaching and research go hand in hand—that success in one depends on success in the other—and that a modern university must do both well. He also believed that sharing our knowledge and discoveries would help make the world a better place. In 145 years, we haven’t strayed from that vision. This is still a destination for excellent, ambitious scholars and a world leader in teaching and research. Distinguished professors mentor students in the arts and music, humanities, social and natural sciences, engineering, international studies, education, business, and the health professions. Those same faculty members, along with their colleagues at the university’s Applied Physics Laboratory, have made us the nation’s leader in federal research and development funding every year since 1979. That’s a fitting distinction for America’s first research university, a place that has revolutionized higher education in the U.S. and continues to bring knowledge and discoveries to the world.

Industry

Colleges, universities, and professional schools

Company size

10,000+ Employees

Headquarters location

Baltimore, MD, US

Year founded

1876

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