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Internship Ai Annotation Writing Jobs (NOW HIRING)

Innodata Inc.

$75 - $80/hr

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 ...

Bot Auto

Data Annotation Specialist

Houston, TX · On-site

High-quality data is the lifeblood of our "Physical AI" and the foundation of our autonomous ... Outstanding verbal and written communication abilities; ability to clearly explain complex visual ...

Besimple AI

Strategic Projects Lead -- Audio Data

$53 - $71.75/hr

Required : • 3-7+ years of experience in data operations, AI data delivery, annotation operations ... write clear instructions, guidelines, SOPs, customer updates, and internal product specs. • ...

Q Analysts

Data Annotation Technician

Kirkland, WA · On-site

... AI) and machine learning (ML). Q Analysts is headquartered in San Jose, CA with a presence ... Strong written grammar skills * Professional verbal and written communication * Able to make ...

GE HealthCare

Data Manager - AI Development

$94K - $141K/yr

Track annotation progress, throughput, and quality metrics. * Maintain annotation dashboards to ... Strong written and verbal communication skills, with the ability to translate technical needs into ...

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Internship Ai Annotation Writing information

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How much do internship ai annotation writing jobs pay per hour?

As of Jul 22, 2026, the average hourly pay for internship ai annotation writing in the United States is $15.54, according to ZipRecruiter salary data. Most workers in this role earn between $12.50 and $17.55 per hour, depending on experience, location, and employer.

What is the difference between Internship Ai Annotation Writing vs Data Labeling Specialist?

AspectInternship Ai Annotation WritingData Labeling Specialist
CredentialsTypically students or entry-level with basic technical skillsOften requires experience with labeling tools and data management
Work EnvironmentInternship setting, often in tech or AI companiesFull-time or freelance roles in data annotation firms or tech companies
Industry UsageCommon in AI development, machine learning projectsUsed across AI, autonomous vehicles, and data-driven industries

Internship Ai Annotation Writing focuses on entry-level tasks like creating annotations for AI training data, often as part of an internship program. Data Labeling Specialist involves more experienced data annotation work, often with specialized tools and higher accuracy requirements. Both roles are essential in AI development but differ mainly in experience level and scope.

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Internship Ai Annotation Writing jobs near you
Infographic showing various Internship Ai Annotation Writing job openings in the United States as of July 2026, with employment types broken down into 73% Full Time, 24% Part Time, and 3% Contract. Highlights an 65% Physical, 3% Hybrid, and 32% Remote job distribution, with an average salary of $32,333 per year, or $15.5 per hour.
AI Solutions Engineer

AI Solutions Engineer

Innodata Inc.

On-site, Remote

$75 - $80/hr

Full-time

Posted 12 days ago

Job description

Innodata (Nasdaq: INOD) is a global data engineering company. We believe that data and Artificial Intelligence (AI) are inextricably linked. Our mission is to enable the responsible advancement of artificial intelligence by providing the data, evaluation frameworks, and human expertise required to build AI systems that can be trusted at scale. We provide a range of transferable solutions, platforms, and services for Generative AI / AI builders and adopters. In every relationship, we honor our 36+ year legacy delivering the highest quality data and outstanding outcomes for our customers.
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.
Please be aware of recruitment scams involving individuals or organizations falsely claiming to represent employers. Innodata will never ask for payment, banking details, or sensitive personal information during the application process. To learn more on how to recognize job scams, please visit the Federal Trade Commission's guide at https://consumer.ftc.gov/articles/job-scams.
If you believe you've been targeted by a recruitment scam, please report it to Innodata at verifyjoboffer@innodata.com and consider reporting it to the FTC at ReportFraud.ftc.gov.

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