Senior Mobile Developer
About Me
I am a Senior Mobile Developer with over 9 years of experience in building high-performance Android and iOS applications. My current specialization is in AI-powered mobile solutions, where I combine deep expertise in mobile architecture with practical AI and machine learning implementation. I have extensive experience integrating machine learning models into mobile platforms using Python backend services and JavaScript/TypeScript cross-platform frameworks.
Throughout my career, I have worked on projects for government, enterprise, and fintech sectors, delivering intelligent and responsive applications. I am proficient in native mobile development using Kotlin, Java, Swift, and Objective-C, as well as cross-platform frameworks like React Native and Flutter. My architecture skills include MVVM, Clean Architecture, and Dependency Injection.
I have hands-on experience with on-device machine learning using TensorFlow Lite, Core ML, ML Kit, and PyTorch Mobile, and I am skilled in cloud AI services such as AWS SageMaker, Google AI Platform, and Azure Cognitive Services. My expertise also covers computer vision, NLP integration, and recommendation systems.
On the backend side, I develop Python services using FastAPI, Flask, and Django REST to serve machine learning models, with a focus on scalable deployment using Docker and Kubernetes. I am experienced in API development, data processing, and real-time AI features. Additionally, I am proficient in JavaScript ecosystems, including React Native, Redux, TypeScript, and Node.js.
I am also knowledgeable in cloud and DevOps practices for AI mobile apps, including CI/CD pipelines, monitoring, and security measures such as SSL pinning and model encryption. I have a proven track record of mentoring junior developers and leading AI/mobile integration projects.
I hold a Bachelor’s Degree in Computer Science from Budapest University of Technology and Economics and have earned multiple certifications including TensorFlow Developer Certificate, Google Associate Android Developer, AWS Certified Developer - Associate, and Apple App Development with Swift Certification. I maintain an active Secret Security Clearance valid through 2027, enabling me to work on government and defense projects worldwide.
Skills
JavaScriptKubernetesJavaDockerTypeScriptKotlinReact NativeSwiftReduxFlaskFlutterObjective CFirebaseAWS S3Android Studio
Education
Bachelor of Computer Science
Experience
Developed AI-powered mobile applications using React Native and Flutter, integrating TensorFlow Lite models for on-device image recognition achieving 95% accuracy and 200ms inference time. Built Python FastAPI backend services serving machine learning models to mobile clients, handling 50K+ daily inference requests with 99.9% uptime. Implemented computer vision features in native iOS/Android using Core ML and ML Kit, reducing manual image processing time by 70% for enterprise clients. Created JavaScript/TypeScript SDKs for mobile AI integration, enabling seamless consumption of Python-based ML services across React Native and native mobile apps. Optimized mobile AI model delivery using differential updates and CDN caching, reducing download sizes by 60% and improving user experience.
Architected and developed cross-platform mobile applications with AI features using React Native and TypeScript, integrating with Python microservices for real-time predictions. Implemented chatbot interfaces in mobile apps using NLP models served from Python backends, improving customer support response time by 40%. Developed hybrid mobile/web dashboards using JavaScript visualization libraries (Chart.js, D3.js) to display AI model performance metrics within mobile applications. Created MLOps pipelines for mobile model updates, automating TensorFlow Lite model conversion and deployment to mobile devices via CDN. Mentored junior developers on AI/mobile integration patterns and best practices for secure model serving.
Developed native Android/iOS applications with integrated machine learning features using platform-specific ML frameworks. Built RESTful APIs with Python Flask/Django for mobile backend services, including recommendation engines and predictive analytics. Implemented real-time data processing for mobile applications using WebSocket connections to Python servers. Created proof-of-concept AI mobile applications demonstrating computer vision and natural language processing capabilities.