Newbridge
AI Mobile Application Developer (iOS / Android / Cross-Platform)
Builds and ships AI-powered mobile apps for iOS/Android using Flutter, React Native, or native Swift/Kotlin, integrating LLM APIs (OpenAI, Gemini, Claude), on-device ML (CoreML, TensorFlow Lite, ML Kit), and RAG features like chatbots and computer vision. Day to day involves app development, AI integration, and App Store/Play Store releases with CI/CD.
- Compensation
- Not disclosed
- Location
- Singapore
- Work setup
- Not specified
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- 1+ years
- Category
- Mobile
- Posted
Skills
Must have
- Strong experience in Flutter (Dart) OR React Native OR native iOS (Swift/SwiftUI) / Android (Kotlin/Jetpack Compose)
- Experience with state management (Bloc, Provider, Redux, Riverpod)
- Understanding of mobile architecture (MVVM, Clean Architecture)
- Experience with push notifications, deep linking, in-app purchases, analytics
- Experience with Firebase, SQLite, Realm, Hive
- Hands-on experience integrating LLM APIs (OpenAI GPT-4, Gemini, Claude, Llama) into apps
- Understanding of prompt engineering, RAG, vector DBs, embeddings
- Experience with on-device ML: CoreML, TensorFlow Lite, MediaPipe, ML Kit
- Basic understanding of Computer Vision / NLP / Speech
- REST APIs, WebSockets, GraphQL
- Git, CI/CD (Fastlane, GitHub Actions, Bitrise), App Store deployment
- Degree in Computer Science, AI, Software Engineering or related field
- 8+ years in Mobile Development plus at least 1+ year in AI-integrated mobile apps
Nice to have
- Experience with AI frameworks: Hugging Face, LangChain, LlamaIndex
- Experience with Python for AI prototyping
- Experience building AI chatbot / AI assistant apps
- Experience with Voice AI (Whisper, ElevenLabs) and Vision AI (YOLO, OCR)
- Experience with Edge AI optimization and model quantization
- Published AI-powered apps on App Store / Play Store
- Knowledge of AI safety, guardrails, and compliance
Full description
We are looking for an AI Mobile Application Developer who can build intelligent, AI-powered mobile applications. This role is a mix of Mobile Development + AI/ML Integration + GenAI. You will build apps that use LLMs, Computer Vision, and on-device AI.
Key Responsibilities:
1. Mobile App Development:
- Design, develop, and maintain high-performance mobile applications for iOS and/or Android.
- Build cross-platform apps using Flutter / React Native / Swift / Kotlin.
- Ensure app performance, security, offline capability, and responsiveness.
- Integrate with REST APIs, GraphQL, Firebase, and third-party SDKs.
- Publish and manage apps on App Store and Play Store, including CI/CD.
2. AI / GenAI Integration:
- Integrate AI/ML models into mobile apps - On-device AI (CoreML, TensorFlow Lite, ML Kit) and Cloud AI (OpenAI, Gemini, Claude APIs).
- Build features like Chatbots, AI Assistants, Voice-to-Text, Text-to-Speech, Image Recognition, Recommendation Systems.
- Implement RAG (Retrieval Augmented Generation), prompt engineering, and vector databases (Pinecone, Weaviate) for mobile use cases.
- Work with AI/ML team to optimize and deploy LLMs / SLMs for mobile (model quantization, edge inference).
- Implement real-time AI features - AI camera, document scanner, facial recognition, object detection.
3. Product & Collaboration:
- Collaborate with UI/UX designers, Backend, AI Engineers, and Product teams.
- Translate business requirements into AI-driven mobile experiences.
- Stay updated with latest in GenAI, Mobile AI frameworks, and edge computing.
Required Skills:
Mobile:
- Strong experience in Flutter (Dart) OR React Native OR Native iOS (Swift/SwiftUI) / Android (Kotlin/Jetpack Compose).
- Experience with state management (Bloc, Provider, Redux, Riverpod).
- Good understanding of Mobile Architecture - MVVM, Clean Architecture.
- Experience with push notifications, deep linking, in-app purchases, analytics.
- Experience with Firebase, SQLite, Realm, Hive.
AI / ML:
- Hands-on experience integrating LLM APIs (OpenAI GPT-4, Gemini, Claude, Llama) into apps.
- Understanding of Prompt Engineering, RAG, Vector DBs, Embeddings.
- Experience with on-device ML: CoreML, TensorFlow Lite, MediaPipe, ML Kit.
- Basic understanding of Computer Vision / NLP / Speech.
- Experience with AI frameworks: Hugging Face, LangChain, LlamaIndex is a plus.