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Flexible Remote Image Annotation Jobs in Virginia

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Flexible Remote Image Annotation information

What is flexible remote image annotation?

Flexible remote image annotation is a job where individuals label or tag elements within digital images from a remote location, often from home. This work is crucial for training artificial intelligence and machine learning models, particularly in fields like computer vision and autonomous vehicles. The 'flexible' aspect means workers can often set their own hours and choose tasks according to their availability. Image annotation tasks may include outlining objects, assigning categories, or describing visual content in images. Most positions require attention to detail and basic computer skills, but prior experience is not always necessary.

What are the key skills and qualifications needed to thrive as a flexible remote image annotation specialist?

To thrive as a Flexible Remote Image Annotation Specialist, you need strong attention to detail, visual accuracy, and a basic understanding of image processing, often supported by a high school diploma or equivalent. Familiarity with annotation tools such as Labelbox, CVAT, or VIA, and sometimes experience with basic data entry platforms, is typically required. Excellent time management, communication skills, and the ability to work independently are valued soft skills for this remote role. These skills ensure high-quality, consistent data labeling essential for training reliable machine learning models and supporting AI development.

What are some common challenges faced in flexible remote image annotation roles and how can they be managed?

One common challenge in flexible remote image annotation is maintaining accuracy and consistency across large datasets, especially when guidelines are complex or images are ambiguous. Working independently can also make it harder to get immediate feedback or clarification. To manage these challenges, it’s important to regularly review annotation guidelines, participate in team check-ins or forums, and make use of quality assurance tools provided by the employer. Staying organized and communicating proactively with project leads can help ensure your work meets expectations and deadlines.

What is the difference between Flexible Remote Image Annotation vs Data Labeler?

AspectFlexible Remote Image AnnotationData Labeler
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentRemote, flexible hoursRemote, flexible hours
Industry UsageAI, machine learning, computer visionAI, machine learning, data processing
Job FocusAnnotating images with labels, bounding boxes, segmentationLabeling data, categorizing images or text

Flexible Remote Image Annotation and Data Labeler roles both involve data processing tasks in AI and machine learning industries. While image annotation focuses on marking specific features within images, data labelers may work with various data types, including text and images. Both roles are remote, require similar skills, and serve the same industry needs, but image annotation emphasizes visual data precision.

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Cities in Virginia with the most Flexible Remote Image Annotation job openings:

Flexible Remote Image Annotation jobs near you

Junior/Middle Computer Vision Engineer ID72410

Richmond, VA • On-site, Remote

AgileEngine
Software Development • 201 - 500 employees
Learn more about AgileEngineexternal

Full-time

Posted 18 days ago

Key responsibilities

  • 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

  • Collaborate with senior engineers to analyze model failure cases and identify areas for data or algorithmic improvement

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.