AI Solutions Engineer
$75k - $80k • Hybrid - Washington D.C
Posted 3mo ago
Job Location
Hybrid - Washington D.C
Tech Stack
Remote Work Policy
On-site
Categories
AI Engineer
About the job
Innodata is seeking an AI Solutions Engineer to bring the platform's AI capabilities to life. This role involves integrating synthetic data generation, setting up and tuning annotation tools, and orchestrating reproducible ML workflows. You will collaborate with the Solution Architect and Data/Annotation Engineer to transform raw data into high-quality, model-ready data. The ideal candidate is proficient in modern AI tooling and experienced in deploying sophisticated ML infrastructure in production environments.
Responsibilities
- Configure and validate native AI-assistive features across platform components like Dataset Explorer, DataCard Service, and Annotation Platform.
- Integrate and tune SAM 2 for full-motion video annotation, including object tracking, segmentation calibration, and confidence threshold configuration.
- Implement Frontier model API integration for synthetic data fidelity validation, covering 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.
- Configure NiFi FMV codec validation layer (H.264, H.265, MPEG-4) above the AFS-managed substrate.
- Validate AI feature integration end-to-end across the storefront, annotation platform, and DataCard write-back during Phase C.
Requirements
- Bachelor's degree in Computer Science, Machine Learning, Data Science, or related field (or equivalent experience).
- 6+ years of total professional experience, with at least 4 years in hands-on AI/ML engineering.
- Experience with SAM 2 or equivalent foundation model integration for computer vision or video annotation.
- Experience with Frontier model API integration (OpenAI, Anthropic, or equivalent), including async job management and quality validation pipelines.
- Proficiency in production-grade Python, 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.