Data & Annotation Engineer: CVAT Pipelines & Governance

Innodata; Alexandria (VA); On-site; USD 76,000 - 83,000; Full time

Job summary

Innodata is seeking a Data/Annotation Engineer to manage annotation workflows and ensure data is accurately labeled and fully traceable for model training. You will administer the CVAT toolchain and coordinate with the AI Solutions Engineer to maintain governance of the data corpus.

The role emphasizes detail-oriented work and timely delivery of annotated datasets, including creating documentation for data provenance and ensuring QA readiness within a secure environment.

Qualifications

• Bachelor's degree in Data Science, Computer Science, or related field preferred; 2-for-1 substitute allowed.
• 5+ years total professional experience; 3+ years in data engineering or annotation operations.
• CVAT deployment and day-to-day operation required; not optional.
• FMV annotation concepts and tooling understanding.
• Python scripting for data wrangling, validation, and format conversion.
• Active Secret clearance with TS/SCI eligibility.

Responsibilities

• Receive, validate, ingest, and ontology-map the ODIN 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.

Skills

Python scripting

CVAT

FMV annotation

Data wrangling

Annotation workflows

Data governance

Education

Bachelor's degree in Data Science or Computer Science

Tools

CVAT platform

Databricks

Job description

Innodata is seeking a Data/Annotation Engineer to manage annotation workflows and ensure data is accurately labeled and fully traceable for model training. You will administer the CVAT toolchain and coordinate with the AI Solutions Engineer to maintain governance of the data corpus.

The role emphasizes detail-oriented work and timely delivery of annotated datasets, including creating documentation for data provenance and ensuring QA readiness within a secure environment.