Machine Learning, Python, API Integrations, LLMs, Prompt Engineering

containerization , MLops, Distributed Systems, Logging, LLM-based systems, Alerting, Model observability, Vector databases, Scalable inference systems, Drift detection, Machine Learning Engineering, Orchestration patterns, Model training, Cloud-native architectures, Embeddings, Data ingestion, Experiment tracking, cost tracking, ML platform development, tracing, Feature management, Monitoring, Model registry

Keras, Tensorflow, Frameworks, AWS, Pytorch, Python, Azure, Gcp, model evaluation, feature engineering, data preprocessing, cloud-based ML solutions, MLOps practices, model monitoring

Sql, AWS, Kubernetes, Python, Gcp, Docker, Machine Learning, Kafka, Spark, Llm, RAG, Generative AI models

FastAPI, Sql, Tensorflow, Pyspark, Pandas, Pytorch, Python, Flask, XGBoost, Azure ML, Azure DevOps, scikit-learn, LightGBM

Python, Tensorflow, Machine Learning, Numpy, Pandas, Data Analysis

Jenkins, Bitbucket, Asana, JIRA, Machine Learning, AWS, MySQL, FastAPI, Python, Docker, Flask, Git, Nlp, MongoDB, Generative AI

Scipy, Keras, Pytorch, Deep Learning, Tensorflow, Python, Nlp, Machine Learning, R, scikit-learn, Data Analysis Techniques and Tools