AI Solutions Engineer

Innodata Inc. • Washington, DC

5d • $75 - $80

About The Position

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.

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.

Requirements

• 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 Haves

• 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

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

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level