Tensorflow, MLops, Pytorch, XGBoost, AWS, Python, Kubernetes, Docker, Apis, Microsoft Azure, Google Cloud Platform, Weaviate, LlamaIndex, Prompt Engineering, Semantic Kernel, AI Agents, LangChain, Pinecone, ChromaDB, Scikit-learn, vector databases, Generative AI technologies, Azure AI Search, Conversational AI solutions, microservices architecture, FAISS

, Natural Language Processing, C, Java, Machine Learning, Python, AI frameworks such as PyTorch, Agentic frameworks, R, reinforcement learning, Audio Processing, Generative AI models, Recommendation Systems

Pytorch, FastAPI, Python, Tensorflow, Gradio, Data preprocessing, Model evaluation techniques, Feature engineering, LangChain, MLOps practices, Streamlit, Scikit-learn

System Design, Application Development, Testing, Python, Cloud-native deployment patterns, Operational stability for ML or data-intensive systems

Pytorch, Python, Hugging Face, Experimental Design, evaluation and benchmarking of ML systems, inference cost performance and optimisation techniques, Large Language Models

Unix, Python, Lsf, Bitbucket, Static timing analysis, AI ML, Jenkins, Git, Linux, Splunk, GenAI, cdc, Design Verification, design layout constraints, CI CD process, DesignSync, UPF, SDC, Dft, RDC, EDA Tools, Graph Neural Networks, Implementation, make, reinforcement learning, debug tools, convolutional Networks, Power-aware flows, Clocks, SW development