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Ai Data Annotation Jobs in Virginia (NOW HIRING)

Senior Machine Learning Engineer

Mclean, VA · On-site

$105K - $145K/yr

Experience with data curation/annotation workflows and dataset quality control. * Software ... AI/ML solutions. If you thrive in high-impact environments where you can both build and lead, we'd ...

This role blends remote sensing science with applied data engineering and AI. What You'll Do ... Support annotation workflows by identifying and flagging imagery containing objects of interest

Experience utilizing a myriad of proposal development tools, including AI, as a force multiplier ... annotation, and color review milestones * Identify and flag proposal risks - staffing gaps, unclear ...

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Ai Data Annotation information

What is an AI data annotation?

An AI Data Annotation job involves labeling or tagging data, such as text, images, audio, or video, to train machine learning models. Annotators ensure that data is accurately categorized so AI systems can learn to recognize patterns and make predictions. This work is crucial for improving AI applications like self-driving cars, chatbots, and image recognition software. It often requires attention to detail and familiarity with specific annotation tools.

What does an AI data annotation do?

As an AI Data Annotator, your typical day involves labeling and tagging data such as images, audio, or text according to specific project guidelines, often using specialized annotation software. You may work independently or as part of a remote or on-site team, collaborating with data scientists and quality assurance specialists to ensure consistency and accuracy. Regular feedback sessions and quality checks are common to maintain high annotation standards. The role can be repetitive, but attention to detail and clear communication with team members help create datasets that are crucial for training effective AI systems.

What are the key skills and qualifications needed to thrive in AI data annotation?

To excel in AI Data Annotation, you need strong attention to detail, data accuracy, and a basic understanding of data labeling concepts, typically supported by a high school diploma or equivalent. Familiarity with annotation tools such as Labelbox, Supervisely, or similar platforms is often required, and some employers may value basic programming or machine learning course certifications. Excellent communication, the ability to follow detailed guidelines, and time management are valuable soft skills in this role. These skills ensure the production of high-quality annotated datasets, which are critical for training reliable AI and machine learning models.

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

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

What are popular job titles related to Ai Data Annotation jobs in Virginia?

For Ai Data Annotation jobs in Virginia, the most frequently searched job titles are:

Infographic showing various Ai Data Annotation job openings in Virginia as of August 2026, with employment types broken down into 1% As Needed, 78% Full Time, 19% Part Time, and 2% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution.

Junior/Middle Computer Vision Engineer ID72410

Richmond, VA • On-site

AgileEngine
Software Development • 201 - 500 employees

Full-time

This job post has expired today. Applications are no longer accepted.


Job description


AgileEngine is an Inc. 5000 company that creates award-winning software for Fortune 500 brands and trailblazing startups across 17+ industries. We rank among the leaders in areas like application development and AI/ML, and our people-first culture has earned us multiple Best Place to Work awards.
WHY JOIN US
If you're looking for a place to grow, make an impact, and work with people who care, we'd love to meet you!
ABOUT THE ROLE
We are looking for a Junior/Middle Computer Vision Engineer to support high-volume execution across data preparation, model training, and evaluation for an AI team working with large-scale image and video datasets. You will curate and manage annotation workflows, run model training and evaluation jobs, maintain benchmarks, and collaborate with senior engineers on failure-case analysis. The role offers a a clear growth path into applied modeling or MLOps for an early-career engineer eager to build hands-on AI experience.
WHAT YOU WILL DO
- Curate large-scale image and video datasets, manage labeling processes and workflows, and ensure the highest standards for dataset quality;
- Run model training and evaluation jobs, ensuring experiments are executed smoothly and efficiently;
- Document training results, maintain ongoing evaluation benchmarks, and track model performance over time;
- Collaborate with senior engineers to analyze model failure cases and identify areas for data or algorithmic improvement;
- Take ownership of foundational tasks that support the broader team's AI/ML lifecycle, directly contributing to the speed and success of production deployments.
MUST HAVES
- You must be authorized to work for ANY employer in the US (e.g., Green card holders, TN visa holders, GC EAD, H4 EAD, U4U with EAD), as we are unable to sponsor or take over employment visa sponsorship at this time;
- 1 to 3 years of experience in software engineering, data science, machine learning, or a related field;
- Degree in Computer Science, Data Science, Engineering, Mathematics, or a related discipline (or equivalent practical experience);
- Engineers located in the US must reside in Dallas, TX, and be open to working from the office (onsite);
- Foundational coding skills in Python;
- Foundational understanding of machine learning concepts and workflows;
- Basic knowledge of computer vision principles (e.g., image processing, object detection basics);
- Basic familiarity with cloud environments and compute resources;
- A strong, demonstrable willingness to learn and adapt in a fast-paced, mentorship-driven environment;
- Excellent attention to detail, specifically regarding data quality and documentation;
- Upper-intermediate English level.
PERKS AND BENEFITS
- Professional growth: Mentorship, TechTalks, and personalized growth roadmaps.
- Competitive compensation: USD-based pay with education, fitness, and team activity budgets.
- Exciting projects: Modern solutions with Fortune 500 and top product companies.
- Flextime: Flexible schedule with remote and office options.