Machine Learning, Apis, Kafka, Microservices, Tensorflow, Git, Pytorch, Gcp, Docker, Opencv, Spark, Databricks, Azure, Kubernetes, Python, AWS, DevOps MLOps practices, Airflow, data pipelines, MLflow, ONNX, AI-assisted engineering tools, CI CD pipelines

pruning , Hive, Python, XGBoost, Spark, feature engineering, monitoring ML LLM systems, scikit-learn, modern LLM tooling, large-scale data pipelines, LangChain, UDFs, feature selection

Python, GenerativeAI, LLM RAG

LLMs (OpenAI, Data Processing & Feature Engineering, Cloud Platforms (AWS/Azure/GCP – optional), Python, Pytorch, LangChain, NLP Concepts

text classification , Embedded Linux, Nlp, Pytorch, Python, LLM RAG Pipelines, LangChain, Hugging Face, TensorRT, Quantization, Model Fine-tuning, NVIDIA Jetson Platforms, ONNX, Vector Databases, Jetson Nano, ONNX Runtime, LLM Deployment, RAG, Real-time AI Applications, Edge AI Optimization, NER, Prompt Engineering

Machine Learning, Python, Sql, Statistical Analysis, Generative AI, R, observability monitoring tools, full-stack development

Python, AI/ML, AI/ML Engineer, Cloud AI

AI ML, Pytorch, Sql, Nlp, aws, Model Deployment

Python, image processing techniques, embeddings, Generative AI, LLMs, Azure OpenAI Service, vector databases, deep learning architectures, conversational AI systems, agent workflows, chatbots, AI pipelines, neural network frameworks, RAG pipelines, retrieval pipelines