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Data Annotation Jobs in Potomac, MD (NOW HIRING)

Welo Data

Data Labeling Associate

Washington, DC

$34/hr

Execute Data labelling and annotation tasks across speech and voice datasets. * Work with audio and language data, including transcription, categorization, and tagging. YOU ARE A FIT IF YOU'RE... * A ...

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Data Annotation information

What is a data annotation?

A Data Annotation job involves labeling and categorizing data, such as text, images, audio, or video, to help train machine learning models. Annotators apply tags, bounding boxes, or classifications to data based on specific guidelines. This process improves the accuracy of AI systems in recognizing patterns and making predictions. Many data annotation jobs require attention to detail and familiarity with specific domains. It is commonly used in applications like autonomous driving, natural language processing, and computer vision.

What does a data annotation do?

A typical workday as a Data Annotator involves reviewing datasets—such as images, audio, text, or video—and accurately labeling or categorizing information according to specific project guidelines. Most Data Annotators work independently, but they often collaborate with project managers or data scientists to clarify requirements and resolve ambiguities. Tasks may be repetitive, but adhering to precise standards is vital for maintaining data quality. Work environments can range from technology companies to remote or freelance settings, and advancement opportunities exist as team leads or quality assurance specialists for those who excel in consistency and reliability.

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

To thrive in Data Annotation, you need strong attention to detail, accuracy, and basic data handling skills, often supported by a high school diploma or equivalent. Familiarity with annotation platforms, data labeling software, or content management systems is frequently required, though specific certifications are rare. Excellent communication, time management, and the ability to focus on repetitive tasks distinguish top performers in this role. These skills are crucial because accurate and consistent data annotation directly impacts the quality of machine learning models and AI applications.

How much money can I make doing data annotation?

Data annotation jobs typically pay between $10 and $20 per hour, depending on the complexity of the task and the employer. Experienced annotators or those working on specialized projects may earn higher rates, especially if they have skills in specific tools or domains. Earnings can vary based on whether the work is freelance, part-time, or full-time, and some platforms offer bonuses for accuracy or speed.

What are the most commonly searched types of Data Annotation jobs in Potomac, MD?

The most popular types of Data Annotation jobs in Potomac, MD are:

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For Data Annotation jobs in Potomac, MD, the most frequently searched job titles are:

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What cities near Potomac, MD are hiring for Data Annotation jobs?

Cities near Potomac, MD with the most Data Annotation job openings:

Data Annotation jobs near you
Infographic showing various Data Annotation job openings in Potomac, MD as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 14% Part Time, and 2% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution.

AI Solutions Engineer with Security Clearance

Innodata Inc.

Washington, DC • On-site

$75 - $80/hr

Contractor

Posted 14 days ago

Innodata rating

7.5

Company rating: 7.5 out of 10

Based on 6 frontline employees who took The Breakroom Quiz

162nd of 244 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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Hours and flexibility

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