ZipRecruiter

Log In

1

Video Annotation Jobs in Washington (NOW HIRING)

next page

Showing results 1-20

All JobsVideo Annotation JobsVideo Annotation Jobs in Washington

Video Annotation information

See Washington salary details

$29.4K

$67.7K

$107.6K

How much do video annotation jobs pay per year?

As of Jun 9, 2026, the average yearly pay for video annotation in Washington is $67,716.00, according to ZipRecruiter salary data. Most workers in this role earn between $52,100.00 and $78,700.00 per year, depending on experience, location, and employer.

What is a Video Annotation job?

A Video Annotation job involves labeling objects, activities, or events within videos to help train machine learning models. Annotators use specialized tools to draw bounding boxes, segment frames, or classify scenes to improve AI's ability to recognize visuals. This work is essential for applications like autonomous vehicles, facial recognition, and action recognition in AI systems.

What are the typical daily responsibilities of a Video Annotation specialist?

As a Video Annotation specialist, your daily tasks will generally involve watching video footage, identifying relevant objects or actions, and accurately labeling or tagging frames according to specific project guidelines. You may also review and validate annotations to ensure quality and consistency, collaborate with team members or project managers to clarify labeling instructions, and document any ambiguities or challenges encountered during annotation. Most roles are structured with clear targets or quotas for completed work, and you may work independently or as part of a larger team supporting AI development projects. The position requires strong concentration and the ability to handle repetitive tasks efficiently while maintaining high standards of accuracy.

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

To excel in Video Annotation, you need strong attention to detail, visual analysis skills, and familiarity with video processing concepts, often supported by a diploma or coursework in computer science or a related field. Knowledge of annotation tools such as CVAT, Labelbox, or VGG Image Annotator, and, in some cases, experience with basic scripting or data management platforms, is highly valued. Excellent focus, time management, and the ability to follow precise instructions help individuals stand out in this position. These abilities are crucial for ensuring the accuracy and quality of annotated video data, which directly impacts AI and machine learning model performance.

What are the most commonly searched types of Video Annotation jobs in Washington? The most popular types of Video Annotation jobs in Washington are:
What are popular job titles related to Video Annotation jobs in Washington? For Video Annotation jobs in Washington, the most frequently searched job titles are:
What job categories do people searching Video Annotation jobs in Washington look for? The top searched job categories for Video Annotation jobs in Washington are:
Video Annotation jobs near you
Machine Learning Engineer - Computer Vision

Machine Learning Engineer - Computer Vision

CaseGuard

Arlington, VA • On-site

Full-time

Posted 28 days ago

Job description

Job Summary:
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. They are seeking a highly skilled and motivated Machine Learning Engineer specializing in Computer Vision to develop and deploy machine learning models focused on image and video processing.
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.
Qualifications:
Required:
• 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.
Preferred:
• 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.
Company:
CaseGuard is the world’s leading AI-powered Redaction and Investigation Solution. Founded in , the company is headquartered in Arlington, Virginia, US, , with a team of 51-200 employees. The company is currently Growth Stage.

Apply