Java, Unix, Sql, Hive, shell scripting, Linux, MySQL, Data Visualization, Oracle, Python, Teradata, R

Machine Learning, Pyspark, Python, Tensorflow, Pytorch, Apis, Artificial Intelligence, Time Series Forecasting, Big Data Ecosystem

Deep neural network models (CNN, Machine learning techniques (regression, Transformers), classification), Tensorflow, Pytorch, Python, Sql, Clustering, Rnn, NLP models and conversational AI solutions, Classical statistical modeling

Machine Learning, Sql, MLops, Python, Statistical Analysis, Semantic Layers, Embeddings, LLM APIs, RAG, Agent Orchestration Frameworks, Feature Engineering, Deployment, Inference, Monitoring

Tensorflow, Pytorch, Python, Graphql, Neo4j, graph-based data modeling, PQ, metadata filtering, Nemotron, natural language query answering, FAISS-based vector indexes, Retrieval-Augmented Generation pipelines, vector databases, HNSW, QLoRA, document chunking, LoRA, IVF, Llama variants, Knowledge Graphs, parameter-efficient fine-tuning, Mistral, Phi

Hadoop, Natural Language Processing, Google Cloud, Sql, Computer Vision, Spark, Python, AWS, ML evaluation techniques, GANs, fine-tuning, Transformers, LLMs, perceptual quality metrics, multimodal learning, deep learning architectures, prompt engineering, generative tasks, R, user-in-the-loop testing, diffusion models

Tensorflow, Hadoop, Pytorch, Pandas, Spark, Python, Sql, Google Cloud, AWS, Scikit-learn