Machine Learning, Tensorflow, Pytorch, Docker, automation, Python, AWS, Git, MLops, Gcp, Azure, Kubernetes, Airflow, Infrastructure as Code, model versioning, MLflow, Kubeflow, model registries, feature stores, DevOps practices, Scikit-learn, Ai, Monitoring, CI CD pipelines, ML model deployment

Docker, Pyspark, Pytest, Azure Databricks, Azure Cloud Services, Python, Sql, MLflow

Prometheus, Gpu, Grafana, Pytorch, Docker, Python, Linux, Kubernetes, embeddings, ML Engineering, tool calling, Hugging Face, LLM Inference, SGLang, LangSmith, Langfuse, RAG LangGraph, quantization, Observability, TensorRT-LLM, KV Cache, vLLM, Agentic AI, TGI, LoRA, RAG, W B, LlamaIndex, QLoRA, AI Infrastructure

AWS, Apis, integrating ML models into production systems, automated testing of model performance and stability, model evaluation techniques, feature engineering, data preprocessing, MLOps tools and frameworks

Spark, Java, Hadoop, Cloudformation, Yarn, Tensorflow, Hive, MLops, Docker, Sns, Python, Kubernetes, AWS, Airflow, Pipelines, H2O, EventBridge, CodeBuild, SageMaker, CodePipeline, CodeCommit, CloudTrail

Excel, Python

Numpy, Machine Learning, Pandas, Python, MATLAB, Scikit-Learn

Pytorch, Agile, Kubernetes, Scrum

C Language, R Programming, Python, Unix, Linux, Artificial Intelligence and Machine Learning, Llm

Azure, Gcp, Pytorch, Python, Aws, Llm