Hybrid AI Solutions Engineer - Production ML Pipelines

Innodata Inc.; Washington (District of Columbia); On-site; USD 103,320 - 110,208; Full time

Job summary

Innodata seeks an AI Solutions Engineer to implement production AI capabilities in a secure federal data environment. You will integrate synthetic data generation, tune the annotation toolchain, and orchestrate reproducible ML workflows with the Solution Architect and Data/Annotation Engineer.

Candidates should have 6+ years in AI/ML engineering, strong Python, and experience with SAM 2 and Frontier model API; an active TS/SCI eligibility is required.

Qualifications

• Bachelor's degree or higher in CS/ML/Data Science or related field; Master’s preferred.

Responsibilities

• Configure and validate AI‑assistive features across platform components.
• Integrate SAM 2 for video annotation: tracking, segmentation, thresholds.
• Integrate Frontier model API for synthetic data fidelity validation; manage prompts and quality scoring.
• Configure auto‑labeling and confidence scoring in annotation tools.
• Ensure IA workflows and data governance within the secure DoD/federal environment.
• Validate end‑to‑end AI feature integration across storefront, annotation platform, and DataCard write‑back.

Skills

Python

AI/ML engineering

Data pipelines

Education

Bachelor's degree in Computer Science, ML, Data Science or related field

Master's degree preferred

Tools

SAM 2

Frontier model API

NiFi FMV

CVAT

Job description

Innodata seeks an AI Solutions Engineer to implement production AI capabilities in a secure federal data environment. You will integrate synthetic data generation, tune the annotation toolchain, and orchestrate reproducible ML workflows with the Solution Architect and Data/Annotation Engineer.

Candidates should have 6+ years in AI/ML engineering, strong Python, and experience with SAM 2 and Frontier model API; an active TS/SCI eligibility is required.