ZipRecruiter

Log In

1

Ai Annotation Jobs in Reston, VA (NOW HIRING)

Innodata Inc.

QA / Evaluation Lead

Washington, DC

$45 - $50/hr

... annotation to senior-annotator adjudication * Validate quality scoring and IAA computation within the Innodata data layer * Support AI Solutions Engineer on evaluation design for SAM 2 and Frontier ...

next page

Showing results 1-20

All JobsAi Annotation JobsAi Annotation Jobs in Reston, VA

Ai Annotation information

See Reston, VA salary details

$104.9K

$138.9K

$182.8K

How much do ai annotation jobs pay per year?

As of Jul 23, 2026, the average yearly pay for ai annotation in Reston, VA is $138,942.00, according to ZipRecruiter salary data. Most workers in this role earn between $115,000.00 and $169,500.00 per year, depending on experience, location, and employer.

What is an AI Annotation job?

An AI Annotation job involves labeling, tagging, or annotating data, such as images, text, or audio, to train machine learning models. Annotators help improve AI accuracy by providing high-quality, structured data that algorithms use to learn patterns. Tasks may include identifying objects in images, transcribing speech, or classifying text-based content. This job is essential for developing AI applications like self-driving cars, chatbots, and image recognition systems.

What are the typical daily responsibilities of an AI Annotation specialist?

As an AI Annotation specialist, your typical day will involve accurately labeling, categorizing, or tagging large volumes of images, text, audio, or video data to train AI models according to project guidelines. You may work independently or as part of a team, using specialized annotation platforms and regularly reviewing your work to ensure quality and consistency. Collaboration with data scientists or project managers may be required to clarify ambiguous cases or update labeling criteria. You can expect periodic feedback and performance reviews to help refine your skills and ensure the data meets the project’s standards, making attention to detail and adaptability essential for success.

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

To thrive as an AI Annotation professional, you need keen attention to detail, strong analytical skills, and a basic understanding of machine learning concepts, often supported by a high school diploma or relevant technical training. Familiarity with data labeling tools, annotation platforms such as Labelbox or Supervisely, and basic spreadsheet or database management is commonly required. Strong communication, time management, and the ability to maintain focus during repetitive tasks are standout soft skills. These abilities are crucial for producing high-quality, consistent data that supports the effective development and accuracy of AI models.

What are popular job titles related to Ai Annotation jobs in Reston, VA? For Ai Annotation jobs in Reston, VA, the most frequently searched job titles are:
What job categories do people searching Ai Annotation jobs in Reston, VA look for? The top searched job categories for Ai Annotation jobs in Reston, VA are:
What cities near Reston, VA are hiring for Ai Annotation jobs? Cities near Reston, VA with the most Ai Annotation job openings:
Ai Annotation jobs near you
Infographic showing various Ai Annotation job openings in Reston, VA as of July 2026, with employment types broken down into 75% Full Time, 22% Part Time, and 3% Contract. Highlights an 70% Physical, 3% Hybrid, and 27% Remote job distribution, with an average salary of $138,942 per year, or $66.8 per hour.
Assistant Research Scientist (PREP0004176)

Assistant Research Scientist (PREP0004176)

Johns Hopkins University

Gaithersburg, MD • On-site

Full-time

Posted 15 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 889 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.

What Johns Hopkins Medicine employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

Apply