Data & Annotation Engineer

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 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.

Key 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

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

The expected hourly salary range for this position is $55 to $60 p/hour, based on experience, skills, and qualifications.

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