AI Solutions Engineer
Innodata Inc.2 months ago
Washington, DC, USASenior
Responsibilities
- Configure and validate AI-assistive features across Dataset Explorer, DataCard Service, and Annotation Platform components.
- Integrate and tune SAM 2 for full-motion video annotation, including object tracking, segmentation calibration, and confidence thresholds.
- Integrate Frontier model APIs for synthetic-data fidelity validation, including prompt engineering, response validation, and quality scoring.
- Configure AI-assisted annotation features such as confidence scoring, auto-escalation triggers, and model-assisted label suggestions.
- Implement ICAM/OIDC authentication integration with the AFS identity framework.
- Configure data-layer DLP policies above the AFS-managed DLP infrastructure substrate.
- Configure the NiFi FMV codec validation layer for H.264, H.265, and MPEG-4.
- Validate AI feature integration end-to-end across the storefront, annotation platform, and DataCard write-back.
- Partner with the Solution Architect and Data/Annotation Engineer to produce high-quality, model-ready data.
Requirements
- Bachelor's degree in Computer Science, Machine Learning, Data Science, or a related field, or equivalent experience substituting on a 2-for-1 basis; a master's degree is preferred.
- At least 6 years of total professional experience and 4 years of hands-on AI/ML engineering experience.
- Experience with SAM 2 or an equivalent foundation-model integration for computer vision or video annotation.
- Experience integrating Frontier model APIs such as OpenAI or Anthropic, including asynchronous job management and quality-validation pipelines.
- Strong production-grade Python skills and comfort 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.
- Experience with CVAT, DoD or intelligence-community data programs, AI/ML training-data evaluation, video understanding or FMV annotation, and DataCard or ML data-provenance frameworks is preferred.
Benefits
- The role is part of an intensive 20-week program phase.
- The position operates in a secure federal IL4 environment.
- The role does not own infrastructure deployment and focuses on the AI/ML configuration and integration layer.
- Expected hourly salary is $75 to $80 per hour.
Tech Stack
DatabricksPython
Categories
Solutions Engineering