causal inference , Large language models (LLMs), Google Cloud Platform (GCP), Cloud Engineering, Machine Learning, Microsoft Azure, Predictive Modeling, Artificial Intelligence, Python, AWS, Scalable machine learning systems, Counterfactual methods, Research and experimentation, Data streaming pipelines, Retrieval-augmented generation, Real-time inference, Statistical machine learning, Transformer architectures, AI orchestration

Tensorflow, Pytorch, Docker, Python, LangChain, pgvector, Qdrant, MLflow, Pinecone, LlamaIndex

render , Machine Learning, Docker, XGBoost, Python, Sql, Forecasting, LightGBM, Supabase, CatBoost

Gcp, Azure, Python, AWS, vector stores, statistical machine learning algorithms, LLM orchestration, embedding models, ML systems, transformer models

probability , Tensorflow, Git, Nlp, Pytorch, Docker, Predictive Modeling, Python, Kubernetes, Generative AI, fine-tuning, scikit-learn, LLMs, statistical learning, Mathematics, time-series forecasting, calculus, prompt engineering, model evaluation, Optimization, Statistics, Mathematical Modeling, linear algebra

Kafka, Tensorflow, Nlp, Pytorch, MLops, XGBoost, Spark, Python, graph analytics, scikit-learn, fraud-analytics, MLflow, anomaly detection, Flink, big-data tooling, Kubeflow, feature engineering, Fraud Detection, real-time inference, model monitoring

data preparation , prophet , Machine Learning, Sql, Tensorflow, Data Science, Pandas, Pytorch, Docker, Arima, Python, LSTMs, Airflow, scikit-learn, LightGBM, MLflow, time-series forecasting, Sagemaker, AWS Cloud Platform, data quality assessment, Transformers, MLOps tools, statsmodels