-1Role & responsibilities AI/ML Engineer About the Role: We are building an AI-powered food recognition system for our fitness and nutrition app. The goal is to enable users to scan meals, identify food items (especially Indian cuisine), and get an instant nutritional breakdown (calories/macros). Were looking for an AI/ML Engineer who can take full ownership of this project from dataset creation and model development to backend integration and deployment. Responsibilities: 1 Dataset Preparation Collect or curate labeled food image datasets (focus on Indian meals) Organize images into structured folders for training Perform data augmentation, resizing, normalization 2 Model Development Choose and fine-tune a CNN model (e.g., ResNet, EfficientNet, MobileNet) Apply transfer learning for food classification (20+ categories) Optimize for high accuracy and convert to TensorFlow Lite (optional for mobile) 3 Training & Evaluation Train the model on Google Colab, local GPU, or cloud Evaluate using metrics like accuracy, F1 score, and confusion matrix Iterate to improve results based on testing 4 Backend Integration Build REST APIs using FastAPI to serve model predictions Accept image uploads and return predicted food labels with confidence scores Integrate predictions with existing MySQL database 5 Deployment & Support Save and deploy the trained model (.h5 or .tflite) Collaborate with the mobile team (React Native) to connect the API or run on-device predictions Ensure performance, scalability, and reliability in production Mandatory Skills: ML/AI TensorFlow / Keras / PyTorch, Transfer Learning, CNNs Image Processing ImageDataGenerator, Pillow/OpenCV, image augmentation Backend FastAPI (REST APIs) Deployment Model saving/loading, TFLite conversion Database Basic integration with MySQL Cloud/Infra Google Colab, AWS EC2 Versioning Git, GitHub, proper code structuring Preferred candidate profile