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Video Annotation Jobs in Washington (NOW HIRING)

Innodata Inc.

AI Solutions Engineer

Washington, DC

$75 - $80/hr

Integrate and tune SAM 2 for full-motion video annotation: object tracking, segmentation calibration, confidence threshold configuration * Implement Frontier model API integration for synthetic data ...

Innodata Inc.

Data & Annotation Engineer

Washington, DC · On-site

$55 - $60/hr

Full-motion video (FMV) annotation concepts and tooling * Python scripting for data wrangling, validation, and format conversion * Active Secret clearance with TS/SCI eligibility Nice-to-Have ...

Innodata Inc.

QA / Evaluation Lead

Washington, DC

$45 - $50/hr

Experience with FMV / video annotation quality standards The expected hourly salary range for this position is $45 to $50 p/hour, based on experience, skills, and qualifications. Note to Candidates:

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Video Annotation information

See Washington salary details

$29.4K

$67.7K

$107.6K

How much do video annotation jobs pay per year?

As of Aug 12, 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?

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
Infographic showing various Video Annotation job openings in Washington as of August 2026, with employment types broken down into 6% Internship, 49% Full Time, 20% Part Time, and 25% Contract. Highlights an 82% In-person, 6% Hybrid, and 12% Remote job distribution, with an average salary of $67,716 per year, or $32.6 per hour.

AI Solutions Engineer with Security Clearance

Innodata Inc.

Washington, DC • On-site

$75 - $80/hr

Contractor

Posted 8 days ago

Innodata rating

7.5

Company rating: 7.5 out of 10

Based on 6 frontline employees who took The Breakroom Quiz

161st of 243 rated software companies

Job description

About the Program:  Innodata's Federal Practice builds the trusted data layer for critical infrastructure Trust & Safety work. Partnering with a leading systems integrator, we're delivering a modern, governed data services platform in a secure federal (IL4) environment. Over an intensive 20-week phase, you'll help stand up a data services storefront, a DataCard governance framework, synthetic data integration, and Databricks write-back capabilities. About the Role:  As the AI Solutions Engineer, you'll bring the platform's AI capabilities to life. You'll integrate synthetic data generation into the pipeline, stand up and tune the annotation toolchain, and orchestrate reproducible ML workflows that the rest of the team can build on. You'll partner with the Solution Architect and Data/Annotation Engineer to turn raw corpora into high-quality, model-ready data. This role suits an engineer who's fluent across modern AI tooling and enjoys making sophisticated ML infrastructure actually work in production. Key Responsibilities: Configure and validate native AI-assistive features across bundled platform components (Dataset Explorer, DataCard Service, Annotation Platform)
Integrate and tune SAM 2 for full-motion video annotation: object tracking, segmentation calibration, confidence threshold configuration
Implement Frontier model API integration for synthetic data fidelity validation: prompt engineering, response validation, quality scoring
Configure AI-assisted annotation features: confidence scoring, auto-escalation triggers, model-assisted label suggestion
Implement ICAM / OIDC authentication integration with AFS identity framework
Configure data-layer DLP policies above the AFS-managed DLP infrastructure substrate
Configure NiFi FMV codec validation layer (H.264, H.265, MPEG-4) above AFS-managed substrate
Validate AI feature integration end-to-end across storefront, annotation platform, and DataCard write-back during Phase C Must-Have Qualifications: Bachelor's degree in Computer Science, Machine Learning, Data Science, or related field required; Master's degree preferred. Equivalent experience may substitute for degree on a 2-for-1 basis.
6+ years total professional experience, 4+ years hands-on AI/ML engineering
SAM 2 or equivalent foundation model integration for computer vision or video annotation
Frontier model API integration (OpenAI, Anthropic, or equivalent): async job management, quality validation pipelines
Python — strong, production-grade; comfortable with ML tooling and data pipeline development
Experience configuring AI-assistive features in annotation platforms or ML data tooling
Active Secret clearance with TS/SCI eligibility Nice-to-Have Qualifications: CVAT annotation platform — AI feature configuration and operation
DoD or IC data program experience: CUI, distribution statements, federal data governance
Evaluation design for AI/ML training data: IAA methodology, drift detection, model performance measurement
Video understanding or FMV annotation experience
DataCard or ML data provenance framework familiarity The expected hourly salary range for this position is $75 to $80 p/hour, based on experience, skills, and qualifications. Note to Candidates:  This role does not own infrastructure deployment. The AI Solutions Engineer operates at the AI/ML configuration and integration layer above the infrastructure. The ideal candidate is equally comfortable writing Python integration code and reasoning about model quality — and understands that in a federal data environment, every AI decision needs an audit trail.

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