AI / ML & Backend Systems Intern

The Opportunity At Textify.ai↗, we are bridging the gap between sophisticated machine learning models and seamless user experiences. We are looking for an AI/ML Intern with a strong Backend foundation—someone who doesn't just build models in a vacuum but understands how to serve them, optimize them for mobile, and manage the data architecture behind them. This role is perfect for a developer who enjoys the "full-stack" of AI: from training and quantizing models to deploying robust APIs and managing hosting environments.

Technologies (Learning & Hands-On)

• AI/ML: TensorFlow, TensorFlow Lite (TFLite), Keras, Model Optimization.
• Backend: Python, FastAPI / Flask, Pydantic, RESTful API Design.
• Database & Hosting: PostgreSQL / MongoDB, Redis, Docker, Cloud Hosting (AWS/GCP).
• Mobile Integration: On-device ML execution, Model Quantization.

What You Will Do

• On-Device AI Optimization: Use TensorFlow Lite to convert and optimize models for mobile deployment, ensuring high performance and low latency on Android devices.
• Robust Backend Development: Build and maintain scalable REST APIs using Python/FastAPI to handle high-frequency AI requests and data processing.
• System Architecture: Design and manage database schemas and caching layers to ensure data persistence and rapid retrieval for our AI features.
• Deployment & DevOps: Take charge of hosting and infrastructure—containerizing services with Docker and deploying them to cloud environments.
• Model Pipeline Management: Bridge the gap between research and production by creating automated pipelines for model serving and monitoring.
• End-to-End Integration: Collaborate with our Mobile Dev team to ensure on-device models and backend APIs work in perfect sync.

What We Are Looking For

• TensorFlow Fluency: Comfortable building, training, and troubleshooting models using TensorFlow; familiarity with the TFLite ecosystem is a big plus.
• Backend Proficiency: Strong Python skills with the ability to create structured, secure APIs and work comfortably with relational or NoSQL databases.
• Infrastructure Mindset: Understanding of how to move a project from localhost to a live server (creating APIs, handling CORS, managing environment variables).
• Data Literacy: Ability to handle data preprocessing, augmentation, and efficient storage for ML workflows.
• Problem-Solver: You enjoy the challenge of making a heavy model run smoothly on a resource-constrained mobile device.

Bonus Points

• Mobile Deployment: You have successfully deployed an ML model (Vision, NLP, etc.) directly onto a mobile app using TFLite.
• DevOps Exposure: Experience with Docker, CI/CD, or managing cloud instances (EC2, Render, etc.).
• Computer Vision Interest: Experience with image processing or real-time video analysis.