Senior AI research engineer for medical imaging, computer vision, spatial AI, and research-to-product execution.
Selected experience includes imaging pipelines, spatial reconstruction, signal classification, and product-ready R&D.
Proof points
Medical imaging AI
Selected experience with imaging workflows and precision model development.
Spatial AI systems
Delivered real-time reconstruction and localization pipelines.
Research to product
Focus on moving prototypes toward practical, NDA-sensitive deployment.
Services
Medical Imaging / Computer Vision R&D
For: Biotech and medical-AI teams
Work on imaging pipelines, model development, and validation for diagnostic and vision systems.
Explore this service →Research Engineering Sprint
For: Product teams and innovation labs
Short-term engineering sprints to test feasibility, validate algorithms, and clarify technical risk.
Explore this service →AI / CV Technical Due Diligence
For: Investors, acquisition teams, and internal product owners
Evaluate AI and computer vision technology, architecture, and deployment readiness.
Explore this service →Selected Work
Medical Imaging AI Pipeline
Medical Imaging AI
Short placeholder summary for medical imaging AI research.
View →Spatial AI & 3D Reconstruction
Spatial AI
Short placeholder summary for spatial AI and 3D reconstruction project.
View →TrackEverything - Object Tracking at Scale
Computer Vision
Short placeholder summary for multi-object tracking system.
View →Radar Signal Classification with Deep Learning
Signal Processing
Short placeholder summary for radar classification model.
View →Best Fit / Not a Fit
Ideal Fit
- Medical imaging or spatial AI research problems
- Teams that need technical R&D toward product delivery
- Work requiring careful handling of NDA-sensitive data
Not a Fit
- Generic marketing copy or agency-style AI buzz
- Simple SaaS integrations with no research requirement
- Projects that need immediate low-cost, one-week delivery
Engagement model
1. Problem review
Define the technical challenge, data availability, and research constraints.
2. Prototype validation
Build and evaluate a focused proof-of-concept with clear success criteria.
3. Deployment planning
Prepare an actionable path from research prototype to production-ready delivery.
Ready to scope a medical imaging, computer vision, or spatial AI project?
Email Amitai