Highly motivated and results-oriented Python developer with a strong foundation in building scalable web applications and data pipelines. Proficient in Django, Flask, and data engineering principles, leveraging AWS cloud services for efficient deployment and management. Adept at problem-solving and collaborating in fast-paced environments.
Practical Applications.
End-to-End AI Solutions.
Model Optimization.
Production Deployment.
Python programming: advanced proficiency, OOP, async/await, pandas, type hints, pydantic
Web framework: Flask, Django, FastAPI, HTML, CSS
Hugging Face: Transformers, datasets, model hub, PEFT integration, accelerate for distributed training
Large language models (LLM): Anthropic Claude, Llama integration, inference optimization, multi-modal capabilities
Fine-tuning: LoRA/QLoRA, supervised fine-tuning, RLHF, domain adaptation, parameter-efficient training
Vector databases: Pinecone, Chroma, FAISS, similarity search, index optimization, metadata filtering
Embeddings: OpenAI embeddings, Sentence Transformers, semantic search, text chunking, multi-modal embeddings
Prompt Engineering: Few-shot learning, chain-of-thought, prompt optimization, template management, safety techniques
RAG (Retrieval-Augmented Generation): end-to-end pipelines, document processing, hybrid search, context management, evaluation metrics
Chatbot Development: Multi-turn dialogue, session management, personality design, error handling, API integration
Agentic AI: LangChain, LangGraph, multi-agent systems, tool integration, workflow orchestration
MCP (Model Context Protocol): Protocol implementation, context sharing, interoperability, and integration patterns
Docker: container creation, multi-stage builds, AI workload optimization, GPU-enabled containers, Docker Compose
AWS Cloud: Bedrock, Lambda, S3, EC2, boto3, CloudWatch, and serverless AI deployment