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I am a self-taught Flutter mobile app developer with several years of experience, proficient in creating seamless, high-performance applications across iOS, Android, macOS, Windows, Linux, and the Web. My deep understanding of design patterns, state management, and clean architecture ensures that every project I deliver is robust, scalable, and maintainable. Additionally, I have hands-on experience with publishing apps on both the Google Play Store and Apple App Store, and I’m well-versed in the deployment processes, store requirements, and best practices necessary to get apps successfully released and maintained. Being self-taught, I bring a unique problem-solving mindset, adaptability, and a relentless drive to master new technologies. My background in the events industry has sharpened my troubleshooting skills, allowing me to quickly identify and solve complex issues in development. I specialize in building cross-platform solutions with Flutter, leveraging my expertise in Firebase, APIs, and databasing to create end-to-end applications. Whether you need a responsive mobile app, a desktop solution, or a web application, I’m here to turn your vision into reality with clean code and innovative design. Let’s collaborate to bring your project to life.

I’m a full-stack Flutter developer specializing in building polished, scalable iOS & Android applications, backed by Firebase, Node.js, or client-specific stacks. I’ve worked with multiple clients end-to-end—from early concept and architecture planning through development, publishing, and post-launch iteration. My experience includes production apps with authentication (email, anonymous, PIN-based), real-time databases, push notifications, role-based access control, and multi-tenant architectures. I’ve built apps such as a Flutter affirmation app with dynamic, AI-generated content, a real-time to-do app, and parent–school communication systems featuring chat, ticket routing, and admin dashboards. I’m comfortable owning the full app lifecycle: UI/UX implementation, clean and modular Flutter architecture, backend logic (Firestore, Cloud Functions, Node.js APIs), deployment, and store publishing. I also guide clients through technical decisions, scalability planning, and realistic launch strategies. Beyond client work, I’ve also built and published a custom Flutter iOS haptics package, now used by 100+ developers, giving me hands-on experience with platform channels, native iOS integration, and reusable package design. What I can help you with: * Flutter apps (iOS & Android) * Firebase & Node.js backends * Authentication, databases, and APIs * Real-time features (chat, notifications, live updates) * Clean, maintainable architecture & UX-focused UI * App store publishing and rollout planning I work in a client-oriented, transparent way—clear communication, realistic timelines, and solutions aligned with real business goals. I’m happy to start with a small demo, audit an existing app, or jump on a quick call to align before we begin.

AI has made code easier to produce. It has not made quantitative research easier to trust. A backtest can be generated quickly. Building a research system that produces reproducible experiments, tests generalization, handles large parameter spaces, integrates machine learning correctly, and carries strategy logic safely toward live execution is a different problem. That is the work I specialize in. I design and build serious quantitative research, backtesting, optimization, and trading systems in Python, with particular depth in: VectorBT Pro and Numba Optuna and large-scale hyperparameter optimization Walk-forward testing and chronological cross-validation Robustness analysis and experiment reproducibility Machine learning for trading Market-data infrastructure Signal generation and live trading workflows Research platforms and operational tooling My work is built around the Quantforge Research Engine, my proprietary quantitative research framework. The research engine extends VectorBT Pro into a complete research environment covering the lifecycle around the simulation engine: Define → Validate → Queue → Source data → Simulate → Optimize → Stress-test → Analyze → Reproduce → Generate signals → Trade This gives suitable projects a substantial head start. Instead of billing you to rebuild job queues, data caching, experiment tracking, optimization orchestration, result analysis, ML integration, and trading infrastructure from scratch, I can focus development on what is actually specific to your research. That may include: Your strategy and portfolio logic Custom indicators, signals, stops, sizing, and execution rules Proprietary investment universes and market-selection policies Exchange, broker, or data-provider integrations Custom optimization objectives and search spaces Walk-forward and robustness methodology ML features, labels, models, and decision pipelines Research dashboards and diagnostic tooling Signal generation and production trading workflows The Quantforge Research Engine already supports configuration-driven experiments, multi-source market data, gap-aware caching, multi-timeframe datasets, persistent Optuna studies, smart and grid search, nested optimization, cross-validation, robustness scoring, MLflow model tracking, scalable result analysis, experiment reproduction, queue-based execution, live signals, and persisted trading state, and much more. My primary stack includes Python, VectorBT Pro, NumPy, Pandas, Polars, Numba, Optuna, CatBoost, XGBoost, TensorFlow, Scikit-learn, MLflow, FastAPI, Streamlit, PostgreSQL, MySQL, Redis, Docker, REST APIs, and WebSockets. I am a strong fit if you are seeking: A serious backtesting and quantitative research platform A systematic strategy requiring rigorous optimization and validation An ML-assisted trading research pipeline Infrastructure connecting research, signals, and execution A platform that must support repeatable experiments across strategies, markets, or clients A system that has outgrown notebooks and disconnected Python scripts I am unlikely to be the right developer if you need: A small standalone indicator A quickly assembled trading bot Guaranteed returns or a “profitable AI bot” A disposable prototype with no concern for reproducibility Someone to implement instructions without questioning the research design For a detailed look at the research infrastructure I bring to suitable projects, see the Quantforge Research Engine guide in my Upwork portfolio. I care about whether a strategy has been tested honestly, whether its results can be reproduced, whether optimization is discovering signal or exploiting noise, and whether the live system behaves like the backtest that justified it. If that is also how you think about quantitative development, we should talk.

I build production ready Android & IOS mobile apps for businesses and startups, using Flutter and FlutterFlow, from the early-stage MVPs to internal operational tools. My core stack includes Flutter, FlutterFlow, Dart, Firebase (Auth, Firestore, Realtime Database, Storage, Cloud Functions), REST APIs, and third-party integrations. Recent apps I've built include: 1) A building inspection app with 6 inspection workflows, offline data capture, engineer/admin roles, Firebase syncing, and automated PDF report generation. 2) An air-conditioning business management app with reports, quotations, timesheets, purchase orders, commissioning checklists, calendar workflows, and PDF generation. 3) Firebase-powered apps with authentication, role-based access, file uploads, real-time data, and custom FlutterFlow functionality. What I focus on with every project: — Clean, native-feeling UI on Android and iOS — Scalable Firebase and backend architecture — Real API integrations, not just static screens — Clear communication and realistic timelines — Taking projects from wireframe to Play Store/App Store deployment If you have an app idea, an existing FlutterFlow project that needs fixing, or a business process you want turned into an app, send me the details. I'll review the scope and tell you how I'd approach the build. Outside of client development, I run a technology and software-focused YouTube channel with over 17,000 subscribers, where I create tutorials and educational content around software, development, and technology. Creating technical content has also strengthened my ability to explain complex development decisions clearly, document workflows, and communicate effectively throughout a project.