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Entry Level Ai Data Annotation Jobs in Maryland (NOW HIRING)

Axle

Data Scientist II

Rockville, MD

... annotation, DEG), and Digital Spatial Profiling (annotation, QC, normalization, spatial ... Incorporate AI/LLM-based extraction where appropriate, with clear validation and communication to ...

vetegrity

Senior Data Scientist

Annapolis Junction, MD · On-site

$170K/yr

Roles may include supporting NLP, LLM, and agentic AI initiatives, as well as optimizing data flows ... annotation, model training/validation, and knowledge extraction from unstructured data ...

Omm IT Solutions

Senior Data Scientist

Ellicott City, MD · On-site

... AI libraries like regular expressions (e.g., spacy, langchain), text annotation tools and semantic ... Experience retrieving and manipulating data from a variety of data sources included DB2, Oracle ...

Accenture

Data Protection, A/SA-Evergreen

Baltimore, MD

$84K - $100K/yr

Contribute to emerging areas such as AI and agentic AI security, under guidance. . Qualifications ... Prior internship, academic project, or entry-level experience in security or compliance is a plus.

Sargent & Lundy

Entry Level Civil Engineer

Elkridge, MD

$62K - $90K/yr

Description This entry-level position will offer you the opportunity to utilize and expand your ... using data and modern tools such as automation and AI to improve workflows, reduce rework, and ...

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Entry Level Ai Data Annotation information

What is an entry level AI data annotation?

An Entry Level AI Data Annotation job involves labeling and categorizing data such as images, text, audio, or video to help train artificial intelligence (AI) and machine learning models. Annotators follow specific guidelines to tag data accurately, ensuring that AI systems learn to recognize patterns correctly. These positions typically require attention to detail, basic computer skills, and the ability to follow instructions. No advanced technical knowledge is usually required, making it a great way to start a career in the AI or tech industry.

What are the key skills and qualifications needed to thrive as an entry level AI data annotation specialist?

To thrive as an Entry Level AI Data Annotation Specialist, attention to detail, basic computer literacy, and a high school diploma or equivalent are typically required. Familiarity with data labeling platforms, annotation tools, and spreadsheet software is often expected. Strong organizational skills, focus, and the ability to work independently help individuals excel in this role. These skills ensure accurate and efficient data labeling, which is crucial for developing reliable AI and machine learning models.

What are some common challenges faced by entry level AI data annotation specialists, and how can they be addressed?

Entry-level AI data annotation specialists often encounter challenges such as maintaining consistency and accuracy while labeling large volumes of data, understanding nuanced instructions, and adapting to changing project requirements. These challenges can be addressed by actively seeking clarification from team leads, participating in training sessions, and regularly reviewing annotation guidelines. Collaborating with teammates and using quality assurance feedback also helps improve accuracy and ensures alignment with project standards.

What are the most commonly searched types of Ai Data Annotation jobs in Maryland?

The most popular types of Ai Data Annotation jobs in Maryland are:

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For Entry Level Ai Data Annotation jobs in Maryland, the most frequently searched job titles are:

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What cities in Maryland are hiring for Entry Level Ai Data Annotation jobs?

Cities in Maryland with the most Entry Level Ai Data Annotation job openings:

Entry Level Ai Data Annotation jobs near you
Infographic showing various Entry Level Ai Data Annotation job openings in Maryland 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.

Assistant Research Scientist (PREP0004176)

Johns Hopkins University

Gaithersburg, MD • On-site

Full-time

Re-posted 16 days ago

Johns Hopkins University rating

8.0

Company rating: 8.0 out of 10

Based on 71 frontline employees who took The Breakroom Quiz

191st of 622 rated colleges and universities

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.

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Colleges, universities, and professional schools

Company size

10,000+ Employees

Headquarters location

Baltimore, MD, US

Year founded

1876

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