AI Solutions Engineer

Innodata; Fairfax (VA); On-site; USD 103,320 - 110,208; Full time

Job summary

Innodata’s Federal Practice invites you to join as AI Solutions Engineer to help stand up a data services storefront, DataCard governance, synthetic data integration, and Databricks write-back capabilities over a 20-week phase.

You will configure AI-assisted features across Dataset Explorer, DataCard Service, and Annotation Platform, integrate SAM-2 for video annotation, Frontier API, and ensure end-to-end validation in Phase C.

Qualifications

• Bachelor’s degree in Computer Science, Machine Learning, Data Science, or related field required; Master’s preferred.
• 6+ years total professional experience, 4+ years hands-on AI/ML engineering.
• Experience integrating SAM 2 or equivalent foundation model for computer vision or video annotation.
• Experience with Frontier model API integration (OpenAI, Anthropic, or equivalent), including async job management and quality validation pipelines.
• Strong production-grade Python skills; comfortable with ML tooling and data pipeline development.
• Experience configuring AI-assisted annotation features in annotation platforms or ML data tooling.
• Active Secret clearance with TS/SCI eligibility.

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.

Skills

Python

AI/ML engineering

Data pipelines

SAM-2

Frontier model API

Async jobs

Annotation platforms

ML tooling

Education

Bachelor's degree in CS/ML/DS

Master’s degree preferred

Tools

CVAT

Databricks

NiFi

Job description

Innodata (Nasdaq: INOD) is a global data engineering company dedicated to enabling responsible AI. Our Federal Practice builds a trusted data layer for critical infrastructure Trust & Safety work.

About the Program

Innodata’s Federal Practice delivers a modern, governed data services platform in a secure federal (IL4) environment. Over a 20‑week phase, you will help stand up a data services storefront, a DataCard governance framework, synthetic data integration, and Databricks write‑back capabilities.

About the Role

As an AI Solutions Engineer, you will bring the platform’s AI capabilities to life, integrating synthetic data generation into the pipeline and setting up an annotation toolchain that others can use to build ML workflows.

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 preferred. Equivalent experience may substitute on a 2‑for‑1 basis.
• 6+ years total professional experience, 4+ years hands‑on AI/ML engineering.
• Experience integrating SAM 2 or equivalent foundation model for computer vision or video annotation.
• Experience with Frontier model API integration (OpenAI, Anthropic, or equivalent), including async job management and quality validation pipelines.
• Strong production‑grade Python skills; 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

• Experience with the CVAT annotation platform and AI feature configuration.
• 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.

Salary Range

The expected hourly salary range for this position is $75 to $80 per hour, based on experience, skills, and qualifications.

As set forth in Innodata Inc.’s Equal Employment Opportunity policy, we do not discriminate on the basis of any protected group status under any applicable law.