Data & Annotation Engineer

Role Summary

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.

As the Data/Annotation Engineer, you'll be hands-on with the data itself. You'll administer the annotation toolchain, manage annotation workflows across the corpus, and produce the per-dataset documentation that feeds our governance framework. You'll work with the AI Solutions Engineer to ensure the data going into our models is accurate, well-labeled, and fully traceable. This role is for someone detail-obsessed who understands that great AI starts with disciplined, well-governed data.

Note to Candidates

Phase D corpus production (Weeks 17–19) is the core demonstration deliverable. Candidates must be genuinely comfortable operating CVAT at production quality against a mission dataset under a milestone deadline

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Responsibilities

• Receive, validate, ingest, and ontology-map the ODIN mission-aligned corpus from AFS delivery
• Produce the ODIN load report: corpus description, ontology mapping, readiness state
• Configure CVAT annotation pipeline against the Phase 1 starter kit rule pack
• Operate both self-service and lightweight white-glove annotation paths during Phase D corpus production
• Produce 50–100 label demonstration corpus across synthetic and mission-aligned content
• Support QA/Evaluation Lead on QC execution and corpus annotation dry-runs
• Associate DataCard provenance records with annotated and synthetic outputs in coordination with the Solution Architect

Requirements

Must-Have Qualifications

• Bachelor's degree in Data Science, Computer Science, or related field preferred. Equivalent experience may substitute for degree on a 2-for-1 basis.
• 5+ years total professional experience, 3+ years in data engineering or annotation operations
• CVAT — deployment and day-to-day operation required; this is not a nice-to-have
• Annotated dataset ingest pipelines: schema mapping, format validation, ontology alignment
• 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 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
• 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

About the Company

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.