Machine Learning (ML), FastAPI, Python, Uvicorn, Distributed high throughput and low latency architecture

Fine-tuning and retrieval-augmented generation (RAG) workflows, Python, Security compliance and ethical use of LLMs, LLM pipelines, CI/CD pipelines, Machine learning frameworks, Model validation testing, Machine Learning Operations, Prompt management and versioning systems, Observability tools for LLM applications, Multi Cloud skills

graph databases , C#, Machine Learning, Neo4j, Python, Java, GenAI, Hugging Face, GLM, ASTs, Arango DB, LangGraph, Qwen, Agentic frameworks, RAG architectures, LangChain, LLMs, Ai, LSP, vLLM, AutoGen, Ollama, DeepSeek, Llama, Tree-sitter, OpenAI

Tensorflow, Numpy, Git, Pandas, Pytorch, Gcp, Docker, FastAPI, Azure, Python, AWS, LangChain, scikit-learn, Qdrant, vector databases, Pinecone, async, LangGraph, Chroma, FAISS, RAG, Milvus, Weaviate

Machine Learning Algorithms, Python Programming, Prompt engineering, Data pipelines, Feature engineering

Apache Spark, Sql, Tensorflow, Pytorch, Databricks, Python, Machine Learning Algorithms, model versioning, deep learning frameworks, Lakehouse architectures, cloud platforms, vector databases, embedding models, MLflow, Monitoring, MLOps practices, Statistical Modeling, semantic search architectures, drift detection, CI CD for ML, automated retraining

Nlp, Pytorch, Python, Prompt engineering, RAG architecture, transfer learning, production AI solutions, Hugging Face, LLM fine-tuning techniques, model deployment, PEFT adapters, LoRA, Transformers, LLM orchestration, Transformer architectures