Tensorflow, Pytorch, Gcp, Docker, Azure, Kubernetes, Python, AWS, LangChain, CrewAI, Qdrant, Hugging Face, Pinecone, vLLM, Semantic Kernel, AutoGen, LangGraph, Chroma, Ollama, Milvus, LlamaIndex

AWS, Python, Azure, Gcp, Data storage query optimization, Python microservices containerization, ML modeling calibration, MLOps lifecycle management

Neural Networks, Image Processing, Deep learning techniques, Python Programming Language, Cloud AI services

Continuous Delivery, large-scale backend software platforms, AI ML or Data, strategic roadmap for products and platforms, agile software development methodologies, distributed development teams

Artificial Intelligence, Machine Learning, Core Python, Python, Generative AI, Large Language Models, Llm, Generative AI Applications, RAG, Retrieval-Augmented Generation

MLops, Gcp, Docker, Distributed Systems, Azure, Kubernetes, AWS, feature management, experiment tracking, machine learning systems, ML platform architecture, cloud native architectures, model training, data platforms, pipeline orchestration, data ingestion, model lifecycle management, model monitoring

AWS, Microservices, Kubernetes, Python, Azure, Terraform, Airflow, AI technologies, ML-driven products

Pandas, Sql, Keras, Tensorflow, Numpy, Rest Apis, AWS, Pytorch, Python, Azure, Gcp, Docker, Scikit-learn

Logging tools, Continuous Integration, Continuous Deployment, Prometheus, Networking, Python, Docker, Shell script, Automation Scripting, Elk Stack, Google Cloud Platform, Infrastructure as Code, GCP Native Services, Containerization technologies, Firewall configurations

API design, Grafana, Api Development, Distributed Systems, Prometheus, Kubernetes, Python, RAG pipelines, offline evaluation jobs, LLM APIs, OpenTelemetry, distributed tracing, embeddings, reranking, GCP tooling, LangChain, feature stores, ML system fundamentals, LangGraph, backend programming languages, batch pipelines, vector similarity, evaluation metrics, Vector DBs, retrieval quality, metadata systems, observability stacks