data engineering , Neural Networks, large-scale data processing frameworks and tools, data pipeline development and management in cloud and on-premise environments, AI-driven image processing, generative AI models, deep learning architectures, AI model integration and deployment techniques

Deduplication, Git, Pytorch, Linux, Python, dataset quality, Data Processing, machine learning pipelines, Hugging Face, LLM prompting, data leakage prevention, structured outputs, LLM fine-tuning, experiment configurations, retrieval, GPU environments, Annotation

Machine Learning, Cloud Azure, Deep Learning, Tensorflow, Numpy, Pandas, Software Engineering, Pytorch, MLops, Keras, Python, Generative AI, scikit-learn, Data SQL

BigQuery, Sql, MLops, Python, Power Bi, Generative AI, BigQuery ML, Vertex AI, LangChain, Looker

Sql, Tensorflow, Pandas, Pytorch, Spark, Splunk, Python, Monitoring for data and model drift, Scikit-learn, MLflow, Model versioning, Flink, LLM-based agents, Agentic AI, CI/CD for ML, Ciena Blue Planet UAA

Machine Learning, Deep Learning, Pytorch, Docker, FastAPI, Python, AWS, LangChain, Generative AI, LLMs, AI Agents, Hugging Face, LangGraph, Vector Databases, Embeddings, RAG, LlamaIndex, Prompt Engineering

Python Programming, Generative AI, RAG and embeddings, Prompt Engineering