Iaroslav Kovalchuk

About

Backend/ML engineer working on a battery energy storage system operations dashboard: built a Flask backend integrated with OAuth and a separate FastAPI optimization/simulation service, deployed via Docker CI/CD to Azure Container Apps. Strong in productionizing ML (AzureML to batch endpoints) and in performance/scalability patterns (Postgres indexing/JSONB, per-unit data isolation, async throttling + caching for year-long CPU-intensive simulations across 40+ scenarios).

Experience

Education

Key Strengths

• Designed modular Flask backend using feature-based blueprints for parallel development
• Separated compute-heavy simulations into a dedicated FastAPI service (microservices separation of concerns)
• Built CI/CD to push Docker images from GitHub to Azure and deploy as Container Apps
• Implemented mandatory pytest test suite gating production pushes
• Optimized PostgreSQL/SQLAlchemy models with composite indexes and JSONB for complex rate structures
• Implemented robust transaction handling with commit/rollback guards
• Operationalized ML via AzureML + batch endpoints with retraining/inference integrated into backend
• Scaled per-unit workloads using stateless containers and unit-level data isolation
• Reduced CPU contention by throttling simulations with asyncio.Semaphore and caching previously computed results
• Domain experience with battery energy storage system (BESS) operations, forecasting, and optimization simulations