End‑to‑End Design
Production‑Ready
Autonomous Workflows
I focus on building intelligent systems, not isolated models. My work blends backend engineering discipline with modern AI techniques, ensuring that machine learning models are deployable, scalable, observable, and useful in real-world applications. I prioritize system design, data flow, and long-term maintainability.
Django, FastAPI, REST, JWT/Auth, async APIs, service separation, AI‑first backend design.
Classical ML, feature engineering, TF‑IDF, similarity systems, evaluation metrics.
CNNs, transfer learning, VGG16 fine‑tuning, medical imaging pipelines.
LangChain, tool‑using agents, memory, planning loops, Hugging Face models.
Embeddings, vector similarity search, document chunking, semantic retrieval.
Model serving, FastAPI inference layers, integration with production backends.
Full‑stack Django application with authentication, feeds, scalable data models.
LLM‑powered conversational AI using transcripts, embeddings, and semantic search.
Healthcare AI system using fine‑tuned VGG16 CNN on MRI datasets.
Content‑based recommender built using TF‑IDF vectorization and cosine similarity.
Designing APIs that serve ML models reliably at scale.
Understanding how data moves from user input to model inference to output.
Building systems that can evolve as models and tools improve.