Java, Rest Apis, Generative AI, AI evaluation methodologies, Python APIs, Prompt Management, Vector Databases, Agentic AI, Production-grade AI Agents, Multi-Agent Systems, AI ML technologies, Prompt Engineering, Data ingestion pipelines

Deep Learning, Nlp, Machine Learning, MLops, data preprocessing, Cv, model training, retraining, feature engineering, Monitoring, model serving

Jira, Azure ML, Jenkins, Git, Confluence, Databricks, Rest Apis, Python, RAG workflows, CrewAI, LLMs, AI Agents, PydanticAI, event-driven architectures, Codeium, AutoGen, LangGraph, WebSockets, GitHub Copilot, Windsurf

Apis, Jira, Jenkins, Azure ML, Git, Confluence, Databricks, Python, LLMs, Codeium, PydanticAI, LangGraph, GitHub Copilot, WebSockets, Autogen Crew, Prompt Engineering, Event-driven architectures, Windsurf

Python, Sql, tree-based models, R, observability monitoring tools, Generative AI tooling, time-series forecasting, classical ML modeling

Neural Networks, Image Processing, Natural Language Processing, Deep learning techniques, On-premises infrastructure, Cloud AI services, Generative AI models

Machine Learning, Apis, Sql, Data Integration, Nlp, Git, Gcp, Docker, Azure, Python, AWS, LangChain, Generative AI, LLMs, AI Agents, Embedding Pipelines, CI CD, LangGraph, Vector Databases, RAG, Prompt Engineering, LlamaIndex

probability , Deep Learning, Testing Frameworks, AI evaluation methodologies, ML algorithms, fine-tuning model adaptation, deploying ML models as APIs, production-quality AI code, vector databases, LLM customization, prompt engineering, AI model monitoring, RAG techniques, AI pipelines, drift detection, LLM architectures, linear algebra, Governance, cloud-native AI architectures

Cuda, Pytorch, Hl7, Dicom, Python, DeepStream, Triton Inference Server, pacs, TensorRT, CNNs, NVIDIA Holoscan, MONAI, Vision Transformers