Python, multi-agent systems, fine-tuning, tool use orchestration, vector databases, automated reasoning workflows, production AI workflows, prompt engineering, Evaluation, MLOps practices, retrieval, model APIs

Cuda, Docker, FastAPI, Azure, Python, AWS, LangChain, Anthropic APIs, vector databases, Pinecone, LLM fine-tuning, FAISS, NVIDIA GPU toolkits

Distributed Systems, Python, multimodal systems, vector databases, Pinecone, custom retrieval layers, Swarm, Chroma, transformer architectures, RLHF, LangChain, CrewAI, AI safety, agent frameworks, AutoGen, LLM fine-tuning, LoRA, MLOps tooling, generative AI models, Milvus, OpenAI, Weaviate, QLoRA, LlamaIndex, red-teaming

data wrangling , Cloud Infrastructure, Containers, Python, vector search systems, LLMs, model training, RAG-based systems, CI CD, document knowledge bases, NLP tasks, traditional ML models, feature extraction, large language models, LlamaIndex

Nlp, Data structures, Deep Learning, Prompt Engineering techniques, Semantic search techniques, Embedding models, Infrastructure setup, AI model inferencing, Parallel Processing, CUDA architecture, Transformer architectures

CDK, Typescript, FastAPI, Python, Terraform, Docker, Flask, OpenAI, LlamaIndex, Google, Azure OpenAI, LangChain, AWS Bedrock, Anthropic

Pytorch, Python, Stable Diffusion, LLMs, LoRA, RAG, ComfyUI, diffusion pipelines, PEFT, quantization, vector databases, real-time streaming generation

Prompt optimization techniques, AI APIs and model deployment, AI-powered BI tools, Vector embeddings and semantic search, Prompt engineering tools and platforms, Model fine-tuning and evaluation techniques, Prompt Engineering