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Datacard Jobs (NOW HIRING)

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:

$70 - $75/hr

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:

Solution Architect

Washington, DC · On-site

$70 - $75/hr

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:

$75 - $80/hr

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 this Role:

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:

$75 - $80/hr

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:

$55 - $60/hr

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:

$50 - $55/hr

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:

QA / Evaluation Lead

Washington, DC · On-site

$45 - $50/hr

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:

$45 - $50/hr

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:

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Datacard information

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$14

$27

$44

How much do datacard jobs pay per hour?

As of Aug 12, 2026, the average hourly pay for datacard in the United States is $27.75, according to ZipRecruiter salary data. Most workers in this role earn between $24.04 and $28.12 per hour, depending on experience, location, and employer.

What are some common challenges datacard operators face when managing high-volume card personalization projects?

Datacard Operators often encounter challenges such as maintaining accuracy and quality control while processing large batches of cards, especially during peak periods. They must troubleshoot equipment malfunctions quickly to avoid delays, and ensure sensitive data is handled securely in compliance with industry standards. Collaboration with IT and quality assurance teams is essential to resolve technical issues and uphold security protocols. Attention to detail and the ability to work efficiently under pressure are key factors for success in this role.

What is the difference between Datacard vs Data Analyst?

AspectDatacardData Analyst
Required CredentialsTypically high school diploma or equivalent; certifications in data management or related toolsBachelor's degree in statistics, mathematics, or related field; often certifications in data analysis tools
Work EnvironmentOffice or data center; primarily administrative and data entry tasksOffice setting; analyzing data, creating reports, and interpreting information
Employer & Industry UsageUsed in financial, healthcare, and government sectors for data managementUsed across industries for data-driven decision making and reporting

While Datacard roles focus on data entry and management, Data Analysts interpret and analyze data to support business decisions. Both roles require familiarity with data tools, but Data Analysts typically have more advanced analytical skills and educational background.

What are the key skills and qualifications needed to thrive as a datacard operator?

To thrive as a Datacard Operator, you need attention to detail, manual dexterity, and an understanding of card production processes, typically supported by a high school diploma or equivalent. Familiarity with Datacard machines, card personalization software, and related security protocols is essential. Strong organizational skills, reliability, and the ability to follow precise instructions make someone stand out in this position. These skills are crucial to ensure accurate, secure, and efficient production of identification or financial cards, maintaining quality and security standards.

What is a datacard?

Datacard jobs typically refer to positions involving the management, production, or technical support of secure identification cards, such as credit cards, ID cards, or access cards. These roles may include operating Datacard machines (a brand known for card issuance solutions), troubleshooting equipment, handling data input, or ensuring card security. Employees may work in industries like banking, government, or corporate security, where the secure issuance and handling of cards is essential. Responsibilities can range from machine operation to software management and customer support related to card services.
More about Datacard jobs
Infographic showing various Datacard job openings in the United States as of August 2026, with employment types broken down into 96% Full Time, 2% Part Time, and 2% Contract. Highlights an 66% Physical, 12% Hybrid, and 22% Remote job distribution, with an average salary of $57,721 per year, or $27.8 per hour.

$75 - $80/hr

Full-time

Re-posted 3 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. 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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