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Ai Annotation Jobs in Virginia (NOW HIRING)

Varsity Tutors

High School Reading Tutor

Norfolk, VA · Remote

$18 - $40/hr

Our AI-powered Tutor Copilot enhances your sessions with real-time instructional support, lesson ... Skilled at teaching close reading, annotation, and analytical response construction for complex ...

Varsity Tutors

High School Reading Tutor

Salem, VA · Remote

$18 - $40/hr

Our AI-powered Tutor Copilot enhances your sessions with real-time instructional support, lesson ... Skilled at teaching close reading, annotation, and analytical response construction for complex ...

Varsity Tutors

High School Reading Tutor

Richmond, VA · Remote

$18 - $40/hr

Our AI-powered Tutor Copilot enhances your sessions with real-time instructional support, lesson ... Skilled at teaching close reading, annotation, and analytical response construction for complex ...

Varsity Tutors

High School Reading Tutor

Blacksburg, VA · Remote

$18 - $40/hr

Our AI-powered Tutor Copilot enhances your sessions with real-time instructional support, lesson ... Skilled at teaching close reading, annotation, and analytical response construction for complex ...

Varsity Tutors

High School Reading Tutor

Alexandria, VA · Remote

$18 - $40/hr

Our AI-powered Tutor Copilot enhances your sessions with real-time instructional support, lesson ... Skilled at teaching close reading, annotation, and analytical response construction for complex ...

Varsity Tutors

High School Reading Tutor

Fairfax, VA · Remote

$18 - $40/hr

Our AI-powered Tutor Copilot enhances your sessions with real-time instructional support, lesson ... Skilled at teaching close reading, annotation, and analytical response construction for complex ...

Varsity Tutors

High School Reading Tutor

Leesburg, VA · Remote

$18 - $40/hr

Our AI-powered Tutor Copilot enhances your sessions with real-time instructional support, lesson ... Skilled at teaching close reading, annotation, and analytical response construction for complex ...

Seekr

Senior Data Scientist

Reston, VA · On-site

The right candidate will work on the design, development, and deployment of AI/ML capabilities for ... Coordinate data collection and annotation efforts for supervised training efforts * Design and ...

Seekr

Senior Data Scientist

Reston, VA

The right candidate will work on the design, development, and deployment of AI/ML capabilities for ... Coordinate data collection and annotation efforts for supervised training efforts * Design and ...

Seekr

Senior Data Scientist

Reston, VA · On-site

The right candidate will work on the design, development, and deployment of AI/ML capabilities for ... Coordinate data collection and annotation efforts for supervised training efforts * Design and ...

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All JobsAi Annotation JobsAi Annotation Jobs in Virginia

Ai Annotation information

See Virginia salary details

$10.7K

$45.3K

How much do ai annotation jobs pay per year?

As of Jun 30, 2026, the average yearly pay for ai annotation in Virginia is $43,637.00, according to ZipRecruiter salary data. Most workers in this role earn between $43,300.00 and $43,800.00 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 the most commonly searched types of Ai Annotation jobs in Virginia? The most popular types of Ai Annotation jobs in Virginia are:
What are popular job titles related to Ai Annotation jobs in Virginia? For Ai Annotation jobs in Virginia, the most frequently searched job titles are:
What job categories do people searching Ai Annotation jobs in Virginia look for? The top searched job categories for Ai Annotation jobs in Virginia are:
What cities in Virginia are hiring for Ai Annotation jobs? Cities in Virginia with the most Ai Annotation job openings:
Ai Annotation jobs near you
Infographic showing various Ai Annotation job openings in Virginia as of June 2026, with employment types broken down into 69% Full Time, and 31% Contract. Highlights an 71% Physical, 3% Hybrid, and 26% Remote job distribution, with an average salary of $43,637 per year, or $21 per hour.

RF Signals and Data Analyst

Quartermaster AI Inc

Arlington, VA • On-site

Full-time

Posted 27 days ago

Key responsibilities

  • Analyze RF event data using IQ derived representations such as spectrograms, waterfall views, PSDs, and metadata to identify, classify, and tag signals of interest.

  • Build and refine high quality labeled datasets for machine learning, ensuring labels are technically defensible, consistent, and auditable.

  • Collaborate with DSP and ML engineers to review false positives, false negatives, and edge cases, and improve labeling standards over time.

Job description

About Us:
At Quartermaster AI, we believe the ocean should be a safe and sustainably managed resource for all. By leveraging cutting-edge AI and robotics, we unlock capabilities that were only recently impossible. Our distributed open-ocean systems enable every vessel to sense, compute, and communicate, enhancing maritime domain awareness for those who need it most.
Role Overview:
Quartermaster AI is seeking an experienced RF Signals Analyst with deep technical roots in communications and signals analysis and characterization to lead our signal characterization and data labeling efforts.
This role focuses on turning real world RF sensor data into structured ground truth for machine learning. You will analyze maritime RF events using spectrograms, waterfall plots, PSDs, metadata, and contextual sources like AIS and camera data when available. You will help define signals of interest, identify interference and host-platform noise, and label signals consistently for model development.
This is a hands-on technical role spanning RF analysis, data labeling, and ML dataset creation, with close collaboration across DSP and ML teams.
Key Responsibilities:
  • Analyze RF event data using IQ derived representations such as spectrograms, waterfall views, PSDs, and metadata to identify, classify, and tag signals of interest.
  • Help define and maintain a scalable maritime RF labeling taxonomy, including signal classes, confidence levels, rejection categories, and ambiguity handling.
  • Build and refine high quality labeled datasets for machine learning, ensuring labels are technically defensible, consistent, and auditable.
  • Identify and document recurring host vessel interference, platform artifacts, and environmental noise to support rejection library development.
  • Collaborate with DSP and ML engineers to review false positives, false negatives, and edge cases, and improve labeling standards over time.
  • Use available contextual data such as AIS, camera imagery, collection metadata, and sensor state to support signal interpretation when appropriate.
Qualifications:
  • 3+ years of experience in one or more of the following: RF signal analysis, SDR-based signal review, EW/SIGINT/ELINT analysis, RF dataset creation, or technical signal characterization.
  • Practical experience working with RF data products such as IQ captures, spectrograms, waterfall plots, PSDs, or other time frequency representations.
  • Experience working with structured labeling, annotation, classification, or technical review workflows where consistency and traceability matter.
  • Comfort working in a Linux-based environment using Python, SDR tools, notebooks, or other RF analysis environments to inspect, organize, and process signal data.
  • Ability to communicate clearly with engineers and translate signal observations into actionable labeling guidance.
  • Experience in maritime RF environments or other cluttered, interference heavy operational environments.
  • Understanding of how label quality, taxonomy design, multi-sensor context (for example AIS, EO/IR, or geolocation), and rejection categories affect downstream ML training and evaluation.
  • Active clearance or ability to obtain and maintain a Secret clearance.

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