Mark – Python, Flask, FastAPI

Video streaming platform that allows cameras to stream video over WebRTC. Main features include live view and video playback with an event management system over MQTT.

• Designed and developed from scratch backend for a streaming project as a solo backend engineer;
• Full ownership of the product - backend, infrastructure and simple frontend for demo;

Platform that allows data operators to annotate video and bunch of other stuff. 10+ services under our team ownership with active feature development and maintenance. Some of them are high-load with RPS reaching 200,000+ during peaks.

Business need: a lot labeled data needed for ML models to train based on it and show better results in production. Service also has an API that allows ML engineers to operate with the data.

• Developed and took under ownership 10+ services with active feature development and maintenance;
• Implemented services for data annotation task management (admin, queues, complex business logic for annotation), event management, authentication and authorization, annotation jobs workers, feature flags management, etc.;
• Conducted zero-downtime replication of 300+ millions of records from PostgreSQL to Redshift;
• Achieved 8x performance for a service to handle 100,000+ RPS by identifying bottlenecks, refining system architecture and implementing targeted optimizations;
• Conducted technical spikes and proof-of-concepts (POCs) to evaluate solutions and improve decision-making for complex engineering tasks;
• Mentored engineers by guiding them through technical challenges, fostering best practices;
• 90%+ tests coverage including unit and integration tests.

The company serves the growing business need for full oversight and management of applied AI.

• Developed a test automation framework for a web-based platform using Selenium and Python, ensuring a scalable and reliable testing process;
• Designed and executed automation scripts, including smoke and regression tests, for both front-end and back-end systems with reporting tools;
• Configured automated test executions in CI, streamlining continuous integration for efficient testing cycles;
• Utilized container technologies to support scalable, containerized testing environments;
• Reported and verified bugs, contributing to improved product quality and effective issue resolution.