Python Programming, CrewAI, LangChain, Document Intelligence, LLMOps, Azure AI Stack, RAG Agentic Frameworks, Logic Apps, Azure Function Apps, RAGAS, Foundry ML, LangSmith, Microsoft Azure PaaS, LangGraph, Vision, AI Search

Machine Learning, Neural Networks, Python, ML Test Management, Automation frameworks and tools, R, Deep learning techniques, Cloud AI platforms and services, End-to-end automated test suites, Generative AI models, Continuous integration and continuous deployment

Unix, Python, Lsf, Bitbucket, Static timing analysis, AI ML, Jenkins, Git, Linux, Splunk, GenAI, cdc, design layout constraints, Design Verification, CI CD process, DesignSync, UPF, SDC, Dft, RDC, EDA Tools, Graph Neural Networks, Implementation, make, reinforcement learning, debug tools, convolutional Networks, Power-aware flows, Clocks, SW development

containerization , PostgreSQL, Deep Learning, Pytorch, XGBoost, Testing, Python, Sql, Version Control, Kubernetes, ML modeling, scikit-learn, Monitoring frameworks, MLflow, Predictive fault incident analysis, Kubeflow, Evaluation frameworks, Time-series ML models, ML infrastructure, YugabyteDB, ClickHouse, LightGBM, anomaly detection, Model serving, Training pipelines, Feature handling

Python, AI/ML, LLM APIs

Golang, Docker, Distributed Systems, PostgreSQL, Cloud Infrastructure, Redis, Python, Kubernetes, AWS, scalable backend architecture

Pytorch, Python, SFT, Hugging Face, UEBA, LoRA, QLoRA, Graph models, Programmatic labelling, Open-source ML contributions, LLM SLM fine-tuning, AI agents with tool use and production workflows, ML over columnar or streaming data, Synthetic data generation, Feature stores, anomaly detection

Terraform, Databricks, Linux fundamentals