data engineering , bayesian inference , Machine Learning, Hadoop, Big Data Technologies, Sql, Tensorflow, Nlp, Pytorch, Spark, Statistical Inference, Python, cross-validation strategies, hyperparameter optimization, Scikit-Learn, dimensionality reduction, R

Python, Sql, R, Visualization Tools, Machine Learning Libraries

SAS, Data Analytics, Python, Machine Learning techniques

triton , Cloud Infrastructure, Pytorch, Docker, Python, Apis, Cuda, Git, Linux, Distributed Systems, Kubernetes, Profiling, Continuous batching, GPU utilisation, Tokenisation, Mixed precision, KV caching, Embeddings, Sampling, Evaluation frameworks, Low-level optimisation, Attention, Inference, Decoding, vLLM, Model serving, Transformers, NCCL, Quantisation, Device placement

Tensorflow, Pytorch, Docker, Python, AWS, Api Development, Git, Azure, Kubernetes, embeddings, scikit-learn, vector databases, automation workflows, model evaluation, ML lifecycle, Deployment, data preprocessing, LLMs, generative AI, retrieval-augmented generation, Monitoring, prompt engineering, RAG, AI agents

Numpy, Machine Learning, Pandas, Data Visualization, Sql, Python, Statistics

Gcp, Data Integration, Microsoft Excel, Python, database solutions, Statistical forecasting methodologies, Advanced statistical analysis, Statistical software packages

Sql, Nlp, Gcp, Spark, Azure, Python, AWS, Computer Vision, LangChain, Generative AI, AI Refinery, Crew AI, Retrieval-Augmented Generation, AutoGen, Vector Databases, Multi-Agent Systems, AI Agent Orchestration, Tool Integration, RAG, Agentic AI Systems, Function Calling