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Ai Data Annotation Jobs in Virginia (NOW HIRING)

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 ...

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 ...

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 ...

... Data QA team to define annotation standards, resolve taxonomy issues, and identify data-quality improvements based on model failure modes. • Independently prototype, evaluate, and deploy AI ...

... Data QA team to define annotation standards, resolve taxonomy issues, and identify data-quality improvements based on model failure modes. • Independently prototype, evaluate, and deploy AI ...

Staff AI Engineer About Us: BlackSky is a real-time intelligence company. We own and operate the ... Collaborate with the Data QA team to define annotation standards, resolve taxonomy issues, and ...

Staff AI Engineer About Us: BlackSky is a real-time intelligence company. We own and operate the ... Collaborate with the Data QA team to define annotation standards, resolve taxonomy issues, and ...

Showing results 41-60

Ai Data Annotation information

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 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 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.

How much do AI data annotators make?

AI data annotators typically earn between $12 and $20 per hour, depending on experience, location, and the complexity of the annotation tasks. Many positions are freelance or part-time, requiring attention to detail and familiarity with annotation tools like Labelbox or CVAT.

How to become an AI data annotation?

To become an AI data annotation specialist, you should have strong attention to detail, basic computer skills, and familiarity with annotation tools such as LabelImg or CVAT. Many roles require a high school diploma or equivalent, and some employers prefer candidates with experience in data labeling or related fields. Training is often provided on the job, and the work can be remote or in-office with flexible schedules.
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 job categories do people searching Ai Data Annotation jobs in Virginia look for? The top searched job categories for Ai Data Annotation jobs in Virginia are:
Infographic showing various Ai Data Annotation job openings in Virginia as of July 2026, with employment types broken down into 1% As Needed, 81% Full Time, 13% Part Time, 1% Temporary, and 4% Contract. Highlights an 86% Physical, 3% Hybrid, and 11% Remote job distribution.

Machine Learning Engineer - Computer Vision

CaseGuard

Arlington, VA • On-site

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 27 days ago


Job description

We are seeking a highly skilled and motivated Machine Learning Engineer specializing in Computer Vision to join our team. The ideal candidate will have a strong background in developing and deploying machine learning models focused on image and video processing. You will work closely with cross-functional teams to design, implement, and optimize vision-based AI solutions to address real-world challenges.
Key Responsibilities:
  • Design, develop, and deploy computer vision models for tasks such as object detection, object tracking, video segmentation, and facial recognition.
  • Optimize and fine-tune deep learning algorithms for real-time performance.
  • Work closely with the software engineers and product teams to identify opportunities for leveraging data.
  • Collect, clean, and preprocess large datasets to prepare for model training and evaluation.
  • Evaluate and optimize machine learning models for accuracy, performance, and scalability.
  • Deploy models into production environments and monitor their performance to ensure reliability.
  • Stay up-to-date with the latest advancements in computer vision and artificial intelligence.
  • Collaborate with cross-functional teams to integrate machine learning solutions into business processes.
  • Document processes, models, and implementations to ensure reproducibility and scalability.

Required Qualifications:
  • Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
  • Experience in deep learning models, their training, and hyperparameter tuning using libraries such as TensorFlow, PyTorch, and Transformers or other Huggingface tools.
  • Experience with data manipulation tools such as Pandas, NumPy, and SQL.
  • Strong programming skills in Python and C++.
  • Experience in MLOps principles and model deployment and instrumentation on cloud platforms such as AWS, Azure, or Google Cloud for model deployment and knowledge with efficient serving tools such as ONNX, triton, and vllm.
  • Proficiency in working with image and video data, including preprocessing and augmentation techniques.
  • Strong understanding of machine learning algorithms, including supervised and unsupervised learning and deep learning.
  • Strong communication skills and the ability to work collaboratively in a team environment.

Great to have:
  • Familiarity with containerization and orchestration tools like Docker and Kubernetes.
  • Experience with version control systems such as Git.
  • Understanding software engineering best practices, including code review, testing, and documentation.
  • Experience with Large Language Models (LLMs) is a great plus.
  • Experience with data annotation tools and processes.

Benefits:
  • Competitive Salary
  • Stock Option
  • Medical, Dental, and Vision Insurance
  • 401K
  • Paid Vacation
  • Ten paid holidays per year
  • Friendly and Learning environment

About CaseGuard
CaseGuard is a software company that helps law enforcement agencies, federal agencies, hospitals, schools, airports, and others manage all their media redaction needs in one easy-to-use redaction software. CaseGuard Studio is one of a kind. Our team is driven by a passion for great software design, creating great products, and creative processes; CaseGuard implements innovative ideas across multiple services and agencies. We invest in people. We nurture skills consistent with our values and our future strategy. Our passionate pursuit of excellence, the application of our creativity to solve our clients' challenges, our technical expertise, and our collaborative spirit are measures of our success.