AI ML, Python, Machine Learning, Gen AI, Langgraph

.NET, Rust, Nlp, Api Management, Python, observability monitoring, Agentic AI frameworks, governance for AI applications, intelligent workflow orchestration, LLM integration workflows, vector databases, compliance architectures, distributed systems design, Generative AI solutions, enterprise integration patterns, microservices architecture, GenAI architectures, data flows

Tensorflow, Pytorch, Docker, Oracle, Python, AWS, Sql, Cuda, Git, Gcp, Neo4j, Keras, Azure, AWS Bedrock, NVIDIA, Google Gemini, Transformer architecture, Mistral, Vertex AI, Diffusion models, Agentic workflows, Graph DBs, GANs, LLaMA 3.0, OpenAI GPT-3.5, Copilot

triton , Pytorch, Docker, FastAPI, Restful Apis, Kubernetes, Python, Sagemaker, document databases, TensorRT, ML technologies

Flux, Cosmos, Tensorflow, Pytorch, Docker, MongoDB, FastAPI, Kubernetes, Computer Vision, LoRAs, SAM, Generative AI, Diffusion Models, Vision Language Models, Hugging Face, Pinecone, Mask2Former, controlnet, GPU-based inference, RF-DETR, Stable Diffusion

BigQuery, Pyspark, Deep Learning, Tensorflow, Sklearn, Numpy, Pandas, Gcp, Keras, Azure, Kubernetes, Statistical Analysis, Python, Computer Vision, AWS, Generative AI, Cloud MCP, Recommendation Systems, Cloud Composer, Agentic AI, R, Vertex AI

Statistical Modelling, Machine Learning, Predictive Analytics, Data Cleaning, Data Quality, Exploratory Data Analysis, Gcp, Data Governance, embeddings, model versioning, Ethics, Optimisation, MLOps practices, model validation, responsible AI principles, model registries, NLP techniques, Deployment, LLMs, privacy considerations, cloud platforms, Monitoring, prompt engineering, automated training inference workflows, GenAI frameworks, feature engineering, CI CD for ML

Azure, Python, AWS, cloud platforms, Claude, AI ML technologies

graph databases , Sql, MLops, Gcp, Docker, Rest Apis, Azure, Kubernetes, Python, AWS, Agentic AI frameworks, NoSQL databases