Cuda, Pytorch, Docker, Linux, Python, AWS, TensorRT, ONNX, NVIDIA Triton, FP16, model quantization techniques, INT8, DALI

Exploratory Data Analysis (EDA), Deep learning architectures (CNNs, probability , Transformers), Tensorflow, Nosql, Pytorch, XGBoost, Python, Sql, Azure ML, Etl, Data preprocessing, Distributed training and scaling ML on large datasets, MLflow, Feature engineering, MLOps workflows, Data annotation tools, Kubeflow, Vertex AI, ML model evaluation, Scikit-learn, Statistics, RNNs, linear algebra

RAG, Python programming language, AWS AI ML services ecosystem, FAST APIs, Machine Learning architectures

Rust, AWS, Cloudformation, FastAPI, Kubernetes, Python, Azure, Gcp, Terraform, Jenkins, Git, Spark, Go, vLLM, GitHub Actions, MLflow, Hugging Face Transformers, LangChain, TorchServe, TF Serving, CI CD pipelines