Alidar Toleubay

Backend Developer

Architected a dedicated integration service for government identity verification (KISC), implementing a hybrid storage strategy with Amazon S3 and local fallback to ensure 99.9% data persistence. Developed a dynamic verification service (flowform) for PII collection, featuring conditional skip-logic for pre-populated data and dual-layer (frontend + backend) validation for IIN and phone records. Designed and implemented a backend service for automated synchronization and API-based distribution of AML/CTF sanctions lists (AFM, UN, OFAC, UK). Enhanced data privacy compliance by implementing a PII filtration layer, ensuring only essential encrypted identifiers are persisted in accordance with regulatory standards. Developed a parallel data processing pipeline for large sanction datasets, significantly improving update speed and throughput. Implemented scheduled synchronization using cron jobs with hourly updates and health-check retries to ensure service reliability and data consistency. Improved verification service reliability by implementing timeout-aware request handling, ensuring APIs return explicit failure statuses instead of unknown responses. Conducted load testing and optimized logging and request tracing to improve system stability and monitoring under peak traffic.

• Ensured 99.9% data persistence through hybrid storage strategy with Amazon S3 and local fallback
• Significantly improved update speed and throughput for large sanction datasets via parallel data processing pipeline

Computer Vision Engineer

Optimized a computer vision model for image orientation detection, reducing inference latency by 60% through model and pipeline improvements. Achieved 10× inference speedup by rewriting performance-critical Python components in C++ and integrating the optimized module into the Python pipeline. Developed a multithreaded real-time video processing pipeline supporting simultaneous camera streams. Implemented camera tilt detection with real-time alerts to prevent incorrect camera positioning and improve user experience. Automated dataset generation by compositing segmented human images into interior scenes with randomized scaling and positioning to simulate diverse camera perspectives. Built a hackathon prototype enabling children with disabilities to control game characters using pedal motion tracking.

• Reduced inference latency by 60% for image orientation detection
• Achieved 10× inference speedup by rewriting Python components in C++