
About Me
A Full Stack AI Engineer builds end to end AI powered applications by combining machine learning, backend engineering, frontend development, and deployment/MLOps. They own the entire lifecycle of an AI feature—from data to model to API to UI.
Responsibilities
1. AI/ML Development
Build, train, fine tune, and evaluate ML models including transformers, CNNs, RNNs, LLMs.
Implement RAG pipelines using vector databases such as Pinecone, Weaviate, or FAISS.
Create data pipelines for preprocessing, feature engineering, and dataset management.
Apply MLOps practices for reproducibility, model versioning, and monitoring.
2. Backend Engineering
Build scalable APIs using frameworks like Django, Flask, or FastAPI.
Integrate AI models into backend services with optimized inference pipelines.
Implement authentication, rate limiting, logging, and caching.
Develop event driven or microservice architectures.
3. Frontend Engineering
Build responsive UIs using React, Next.js.
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$6/hr
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