Machine Learning, Tensorflow, Numpy, Pytorch, Docker, Python, AWS, Sql, Deep Learning, Git, Pandas, Gcp, MLops, Azure, Kubernetes, Langchain, Model monitoring, CI CD, Vector Databases, CrewAI, LLMs, Scikit-learn, Data Processing, Semantic Kernel, Langgraph, RAG, Production model deployment, Azure AI, OpenAI, Prompt Engineering

Nltk, Apache Spark, Tensorflow, Pandas, Pytorch, Gcp, Databricks, Azure, AWS, scikit-learn, mlflow, gensim

Power Bi, Tableau, Sql, Azure ML, Git, Databricks, Deployment Tracking, MLflow, MLOps processes and tools, Lineage, Production support practices, versioning, Model Registry, Reproducibility, Telecommunications environment, Cloud ML platforms, Monitoring

data engineering , Machine Learning, Tensorflow, Pytorch, Docker, XGBoost, Python, AWS, Sql, Git, MLops, Azure, Feature Engineering, ML Pipelines, Model Evaluation, CI CD, Scikit-Learn, LangGraph, Model Deployment, ML Modelling, LangChain, CrewAI, LightGBM, AutoGen, Agentic AI

Machine Learning, Nlp, Pytorch, Docker, Rest Apis, Kubernetes, Python, Hugging Face Transformers, RAG, vector databases

Numpy, Predictive Modeling, Pandas, Amazon Redshift, Python, Aws S3, Jupyter Notebooks, Feature Engineering, Scikit-learn, Traditional Machine Learning, Model Testing and evaluation

Java, Hadoop, Neural Networks, Tensorflow, Deep Learning, Nlp, Git, Pytorch, Gcp, Docker, Spark, Azure, Kubernetes, Python, AWS, Data Analysis, scikit-learn, mathematics, LLMs, Statistical Modeling

Pytest, Cloudformation, Docker, Terraform, Python, Processing, MLflow, SageMaker Pipelines, IaC with CDK, CI CD for ML workloads, Model Registry, GitHub Actions, Batch Transform, CodePipeline, boto3, AWS SageMaker

Numpy, Django, Git, Pandas, Docker, MySQL, PostgreSQL, Flask, FastAPI, Python, scikit-learn

Sql, Tensorflow, Pytorch, Gcp, MLops, Docker, Spark, Azure, Kubernetes, Python, AWS, Generative AI, LLMs, Scikit-learn, Agentic AI, RAG