Tensorflow, Pytorch, Keras, Python, Statistical Analysis, image processing algorithms, machine learning pipelines

Debugging, Deep Learning, Pytorch, Python, Computer Vision, Core ML, LoRA model optimization, Generative AI, Performance profiling, TensorRT, Quantization, ONNX, TFLite, LiteRT

Machine Learning (ML), Artificial Intelligence (AI), Hadoop, Pyspark, Autosys, Sql, Angular, React, Spark, Python, Data Architecture, Metadata Management, DevOps practices, Flink, Copilot AI tool, Distributed data processing, Model context, Platform modernization, Performance optimization, Production support models, CI/CD pipelines, Agentic frameworks and flows, Enterprise controls, Data quality frameworks, Generative AI models, Protocol MCP

Django, Docker, Kubernetes, Python development

Retrieval-Augmented Generation (RAG), Api, Python, Microservices, LangGraph, Langchain, Agentic AI, LLMs, multi-agent workflows, backend services, orchestration pipelines

Databases, Scripting, PowerShell, Prometheus, Grafana, Groovy, Shell, Storage, Terraform, Linux, Kubernetes, Python, Azure DevOps, Log Analytics, GitHub Actions, Azure services, Compute, Application Insights, Azure Monitor, Azure networking

Neo4j, Python, embeddings, AgentCore, AWS Bedrock, knowledge graphs, re-ranking, chunking strategy, prompt-library version-management, Veeva Vault, prompt engineering, RAG engineering, LangGraph, vector stores, VQL, Vault REST API, grounding

containerization , Tensorflow, Git, Pytorch, Docker, Version Control Systems, Keras, Python, LangChain, fine-tuning, LLMs, RAG systems, model deployment, Hugging Face, hybrid search techniques, generative AI tools, prompt engineering, LoRA, QLoRA, LlamaIndex

Pyspark, Apache Spark, Data Warehousing, Kafka, Dimensional Modeling, Sql, ELT, Apache Airflow, Git, Gcp, Terraform, Docker, Databricks, Azure, Python, Kubernetes, AWS, Etl, Apache Iceberg, Generative AI, Delta Lake, Apache Hudi, Large Language Models