Building Fashion AI Infrastructure
FI.Company is building the core Fashion Intelligence layer that will empower small and mid-sized fashion brands to compete with global giants like Shein. If there was ever an opportunity to work on large-scale, multimodal AI systems, this is it.
As a Full-Stack AI Engineer Intern, you’ll work across backend, data, and AI layers—helping architect the systems that power the next generation of fashion technology.
Build and maintain FastAPI-based backend services powering core Fashion AI workflows
Develop ETL pipelines, data ingestion systems, and scalable scraping workflows
Implement IP rotation, proxy management, and data quality checks
Deploy and maintain services on AWS (EC2, S3, Lambda, Amplify)
Work with Docker + PostgreSQL to build robust, documented systems
Maintain and optimize CI/CD pipelines using GitHub Actions
Work with LLMs / vLLMs for text, fashion metadata, and trend-analysis tasks
Build small agents for automating extraction, enrichment, and content-generation workflows
Integrate multimodal models (vision encoders, image-text models, retrieval systems) into production pipelines
Experiment with fashion-specific embeddings, similarity search, and retrieval-augmented features
Assist in optimizing model inference, batching, caching, and evaluation loops
Work closely with AI researchers and fashion experts to ship production-ready AI features
Strong CS fundamentals (DSA, backend concepts)
Experience with Python, FastAPI, SQL, Docker
Familiarity with Crawl4AI / BeautifulSoup / Playwright or similar scraping tools
Exposure to LLMs, vector databases, or basic AI agent frameworks
Understanding of modern ML workflows (HuggingFace, OpenAI, vLLM, LangChain, etc.)
Big curiosity, high ownership, and eagerness to learn fast—even when things break :)