Building scalable backend systems, intelligent APIs, and production-ready AI/ML applications.
I'm a Python Backend & AI/ML Engineer with 6+ years of experience building scalable backend services, intelligent APIs, data pipelines, and production AI/ML systems.
- 🐍 Building production systems with Python, Django & FastAPI
- 🤖 Developing LLM, RAG & AI-powered backend applications
- 🧠 Productionizing ML models through real-time inference APIs
- ⚡ Designing REST APIs, microservices & distributed systems
- 📊 Building data & ML pipelines with Airflow, PySpark & Kafka
- ☁️ Deploying cloud-native applications with AWS, Docker & Kubernetes
- 🔧 Focused on scalability, performance, reliability & clean architecture
Django REST Framework · Pydantic · Celery · REST APIs · Microservices
LLMs · RAG · Embeddings · Vector Search · Prompt Engineering · Model Serving · Real-Time Inference
ETL · Data Pipelines · Feature Engineering · Data Processing
PostgreSQL · MySQL · MongoDB · Redis · Amazon Redshift
AWS · CI/CD · Docker · Kubernetes · GitHub Actions · Linux
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Production APIs integrating LLMs and ML models with structured outputs, validation, caching, retries, authentication, and observability. Tech: |
Retrieval systems with document ingestion, embeddings, vector search, context retrieval, and grounded LLM responses. Tech: |
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Scalable inference services for deploying ML models with validation, versioning, monitoring, and real-time predictions. Tech: |
Production backend architectures with APIs, caching, asynchronous processing, databases, CI/CD, and cloud deployment. Tech: |
Scalable APIs · LLM Applications · RAG Systems · Model Serving · Distributed Systems · ML Pipelines
I enjoy turning AI/ML capabilities into reliable production software through scalable backend architecture, intelligent APIs, data pipelines, and cloud infrastructure.
