Microservices, Docker, Python, AWS, Apis, Node.js, Gcp, Distributed Systems, Azure, Kubernetes, Prompt engineering, Event-driven systems, Go, Embeddings, Function calling, Tool calling, LLM evaluation, Generative AI, LLMs, Vector databases, Applied AI, Agent frameworks, Asynchronous execution, RAG

React, Python, HTML, data pipelines or ETL processes, SDLC engineering best practices, secure development practices, AI-assisted development tools, modern JavaScript, databases and data modelling

Microservices, AWS, Nltk, Node.js, Azure, Gcp, Nlp, Javascript, Restful Apis, LLMs, OpenAI, Claude, Hugging Face, cloud platforms, NLU libraries and tools, Rasa, LLaMA, SpaCy

Data Management, Cuda, Gcp, Azure, Kubernetes, Python, AWS, common ML frameworks, Scientific Python Stack, CI CD

Ml, Apis, Data Architecture, Gcp, Azure, Python, AWS, LLM integration, Ai, prompt engineering, performance optimisation, model evaluation, scalable backend systems

Python, Sql, tree-based models, R, observability monitoring tools, Generative AI tooling, time-series forecasting, classical ML modeling

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

Machine Learning, Databricks, Kubernetes, Python, AI ML engineering concepts, containerisation, CI CD, prompt engineering, cloud-native deployment, AI coding tools, RAG, agentic frameworks, Large Language Models