Vladyslav
Android developer
- Age:
- 24 years
- City of residence:
- Kyiv
- Ready to work:
- Kyiv, Remote
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ANDROID DEVELOPER
Experience
Android Developer · Mobile Growth Platform · Mar 2024 — Present ·
Remote
Contact • Developed and scaled 100+ hybrid Android applications combining native and WebView-
[
• Integrated AppsFlyer for reliable collection and processing of attribution and analytics data
[
• Designed and implemented dynamic content routing systems based on runtime
@vladyslav_kolodii configuration and user context
[
strategies to ensure consistent user experience
• Improved application startup experience by implementing asynchronous configuration
loading and cached-first rendering strategies
• Developed Remote Config–driven architecture enabling real-time behavior updates without
Skills requiring app releases
Core • Collaborated with cross-functional teams to support data-driven product decisions and
Kotlin, Android SDK, Coroutines, feature iteration
• Applied Clean Architecture principles with Kotlin, Coroutines/Flow, and dependency
Flow
injection (Hilt/Koin) for scalable and maintainable codebase
Architecture
MVVM, MVI, Clean Architecture, Android Developer · Dozor Tech · Nov 2024 — Jan 2025 · Contract ·
Dependency Injection (Hilt, Koin) Remote
UI • 3-month contract to deliver a driver-facing navigation modulefor a public-sector
Jetpack Compose, Coil app — scoped, built and handed off within the agreed timeframe.
Networking • Built real-time route tracking with Foreground Service and handled the usual edge
Retrofit, OkHttp, Kotlin cases — GPS drift, signal loss on active routes and aggressive battery savers on
Serialization, REST APIs OEM ROMs.
• Wrote parsers for several backend response formats and normalized them into a
Storage
single route model used across the app.
Room, SharedPrefs, DataStore
Firebase & Analytics AI Trainer — Personal Project · 2026 — In development
Auth, Realtime DB, Remote • Offline AI fitness coach that tracks 6 bodyweight exercises inreal time at 30 FPS
Config, FCM, AppsFlyer, OneSignal using ML Kit Pose Detection. Built a rep-counting state machine on top of raw
landmark data to handle noisy detections and partial-body frames.
Maps & Tools
• Tuned the detection pipeline to hold stable 30 FPS on mid-range devices (Pixel
Google Maps / HERE / OSM SDKs, 6a / Samsung A54-tier) — the baseline I target before adding anything on top.
Git, GitHub Actions CI/CD, Postman • Local-first data layer (Room) with background sync to Firebase; app fully usable
AI / LLM Tools without network.
AI-assisted development, Claude • CameraX pipeline records short clips tied to detected reps for post-workout
Code, MCP replay.
Education
Advanced Kotlin for Android with Jetpack Compose
SoftServe
Android Development
IT Step Academy
I am also currently developing my own KMP (Kotlin Multiplatform) platform for financial analytics and
AI-powered insights, so I understand the challenges of building a product from scratch, rapid MVP
delivery, and further scaling.
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