Machine Learning, Natural Language Processing, Kafka, Tensorflow, Django, Pytorch, Gcp, MLops, Docker, Flask, Azure, Python, Kubernetes, AWS, GenAI

Rest Apis, AWS, Pytorch, FastAPI, Python, Azure, Gcp, Flask, Git, CI CD for ML, LLMs, MLflow, Hugging Face Transformers, LangChain, Weights Biases, Generative AI, Transformers

Sql, MLops, AWS, Python, Microsoft Azure, LangChain, Milvus, LlamaIndex, LLMOps, Weaviate, Vector Databases, Pinecone, FAISS, Chroma, Generative AI

Apis, Python, Testing, Gen AI, LLMs, RAG, Prompt Engineering, Deployment, Optimization, Monitoring

AWS, Splunk, Java, Grafana, Dynatrace, Datadog, Gitlab, Prometheus, Kubernetes, Python, Terraform, Jenkins, Scala, Big Data ETL pipelines, observability, SRE best practices

.NET, Containers, Sql, Microservices, Rest Apis, Python, Kubernetes, Azure DevOps, generative AI applications, Infrastructure as Code, NoSQL databases, AI-enabled software engineering practices, CI CD automation, GitHub Actions, Azure Cloud Architecture, modern frontend frameworks, AI LLM solution design and implementation, agentic AI workflows, intelligent automation, event-driven architecture, cloud-native application development