Pytorch, Rust, Cuda, Kubernetes, Python, Spark, TensorRT-LLM, vLLM, inference optimization, Ray, Flink, KV-cache, Go, GKE, speculative decoding, DeepSpeed, memory IO optimization, SGLang, GPU kernel tuning, quantization, FSDP, Megatron

Google Cloud, Tensorflow, Pandas, Pytorch, Microsoft Azure, Keras, Python, AWS, AI Architecture, GANs, RNNs, cloud platforms, deep learning architectures, CNNs, Gen AI

data engineering , object storage , Automated Testing, Microservices, Identity And Access Management, DevSecOps, Distributed Systems, API-first design, modern front-end framework, NoSQL databases, enterprise back-end stack, event-driven integration, CI CD, Messaging, cloud-native engineering, ML AI engineering, full stack application engineering, Caching, Search, Responsible AI, domain-driven design, infrastructure as code

Iot, automation, Devops, Microsoft Azure, Monitoring, Microsoft Fabric, native applications, Ai, cloud-native architecture, intelligent automation, CI CD, observability, Generative AI, digital manufacturing

snowflake , Neo4j, Sql, Databricks, Apache Airflow, Pyspark, Kafka, BigQuery, Redshift, Warehouse internals, Data quality frameworks, dbt, Batch and streaming pipeline design, Delta Lake, Data Engineering fundamentals, Medallion architecture, Data modelling paradigms, Unity Catalog, LangChain, Dimensional data vault, LangGraph

Ml, Authentication, Python, Software Architecture, Apis, Enterprise Applications, generative AI, LLMs, Security, vector search, Ai, cloud platforms, embeddings, CI CD, Source Control, RAG, Authorization

AWS, Cloud Technologies, Git, Version Control Systems, GenAI technologies, machine learning concepts, GitHub workflows

Large Language Models (LLMs), Json, Dynamodb, Sql, Nosql, Jenkins, Xml, Rest Apis, Python, LangChain, CrewAI, Generative AI, PGVector, LangGraph, FAISS, CI/CD, cloud-native architectures, ChromaDB