data engineering , Advanced Analytics, Gcp, MLops, Data Science, Cloud Architecture, Azure, AWS, knowledge graph construction, modern architectures, model fine-tuning, project management, generative AI, AI engineering, AI infrastructure, AI ML systems design, distributed computing frameworks, cloud AI ML services, semantic search architectures, NVIDIA GPU stack

containerization , Cuda, Tensorflow, Pytorch, Docker, Kubernetes, Python, embeddings, fine-tuning, data pipelines, machine learning frameworks, RAG patterns, distributed training, model serving optimization, prompt engineering, NLP transformers, GPU accelerator computing, MLOps tools, cloud-native development

Java, Ranger, Hadoop, Kafka, React, Hive, XGBoost, Spark, Shell scripting, Flask, Keras, Python, MLlib, Hugging Face, Flink, Ozone, Iceberg, Trino, Nifi

data engineering , System Design, cloud solutions, big data platforms, data platforms, data AI ML, Analytics, programming Python, data lakes, ML techniques, ETL processes, ETL pipelines

Python, ROS 2, Isaac Lab, NVIDIA Isaac Sim

data engineering , Git, Apis, Rest Apis, Python, Ai Development

Node.js, Angular, React, Gcp, Elasticsearch, Azure, Python, AWS, CrewAI, Text-to-SQL, knowledge graph design, Strands, CI CD, LangGraph, AutoGen, agentic AI systems, knowledge layer engineering, RAG pipelines, LLM-based applications, infrastructure as code, cloud-native development

pruning , Tensorflow, Pytorch, Pandas, Python, quantisation, model optimisation techniques, knowledge distillation, MLOps tools and practices, AI ML modelling