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Home Based Data Annotation Jobs in Maryland (NOW HIRING)

Proud Moments

In-Home Based BCBA

Rockville, MD · On-site

$90 - $100/hr

Advanced, easy-to-use tools that simplify data collection and charting * The best of both worlds - the resources of a large organization combined with the collegiality and support of the local care ...

Proud Moments

In-Home Based BCBA

Rockville, MD

$90 - $100/hr

Advanced, easy-to-use tools that simplify data collection and charting * The best of both worlds - the resources of a large organization combined with the collegiality and support of the local care ...

Proud Moments

In-Home Based BCBA

Rockville, MD · On-site +1

$90 - $100/hr

Advanced, easy-to-use tools that simplify data collection and charting * The best of both worlds - the resources of a large organization combined with the collegiality and support of the local care ...

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 ...

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 ...

Axle

Data Scientist II

Rockville, MD · On-site

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

CSAA

... Arkansas - Home Teleworkers, California - Home Teleworkers, Colorado - Home Teleworkers ... Support platform modernization and data enablement initiatives , including adopting cloud-based ...

CSAA

... Arkansas - Home Teleworkers, California - Home Teleworkers, Colorado - Home Teleworkers ... Support platform modernization and data enablement initiatives , including adopting cloud-based ...

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Home Based Data Annotation information

Can I do data annotation with no experience?

Home Based Data Annotation jobs often do not require prior experience, as training is typically provided. Basic computer skills and attention to detail are usually sufficient to start, making it accessible for beginners. Familiarity with annotation tools can be helpful but is not always mandatory.

Is it hard to get hired for data annotation?

Home Based Data Annotation jobs typically have moderate competition, and hiring depends on the applicant's attention to detail, accuracy, and ability to follow guidelines. Many positions require basic computer skills and sometimes prior experience with annotation tools, but they often do not demand formal certifications. Candidates who demonstrate reliability and precision have good chances of being hired.

Is data annotation a legitimate job?

Data annotation is a legitimate job that involves labeling data such as images, text, or audio to help train machine learning models. It often requires attention to detail and basic computer skills, and many companies offer remote, flexible positions. However, job seekers should be cautious of scams and verify the legitimacy of employers before applying.

What is the difference between Home Based Data Annotation vs Data Labeler?

AspectHome Based Data AnnotationData Labeler
CredentialsBasic computer skills, attention to detailSimilar; no formal certifications typically required
Work EnvironmentRemote, home-basedRemote or in-office, depending on employer
Industry UsageAI, machine learning, tech companiesAI, machine learning, tech companies
Job TasksAnnotating data for training AI modelsLabeling data for AI training

Both roles involve labeling data for AI systems, often working remotely. Home Based Data Annotation emphasizes working from home with flexible hours, while Data Labeler may work in various environments. Both positions are essential in AI development and share similar skills and industry usage.

How to make 2000 a week working from home?

Home Based Data Annotation jobs typically pay per task or project, and earning $2000 weekly requires completing a high volume of accurately labeled data, often involving skills in image, text, or audio annotation. To reach this income level, consistent work, efficiency, and experience are essential, and some roles may offer bonuses or higher rates for specialized tasks or faster turnaround times.
What are the most commonly searched types of Data Annotation jobs in Maryland? The most popular types of Data Annotation jobs in Maryland are:
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What job categories do people searching Home Based Data Annotation jobs in Maryland look for? The top searched job categories for Home Based Data Annotation jobs in Maryland are:
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Home Based Data Annotation jobs near you

Assistant Research Scientist (PREP0004176)

Johns Hopkins University

Gaithersburg, MD • On-site

Full-time

Re-posted 22 days ago

Johns Hopkins Medicine rating

7.5

Company rating: 7.5 out of 10

Based on 205 frontline employees who took The Breakroom Quiz

231st of 890 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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