Github, Apis, Tensorflow, Numpy, Git, Pandas, MLops, Pytorch, Docker, Azure, Kubernetes, Python, AWS, agentic architecture, GenAI, scikit-learn, LLMOps, Llm, distributed services, infrastructure as code

Distributed Systems, LangChain, policy enforcement, LLMs, agent orchestration frameworks, LangGraph, ML platforms, cost controls, observability, Pipelines, embeddings, retrieval

Apache Spark, Sql, Tensorflow, Pytorch, Databricks, Python, Machine Learning Algorithms, model versioning, deep learning frameworks, Lakehouse architectures, cloud platforms, MLflow, Monitoring, MLOps practices, Statistical Modeling, drift detection, CI CD for ML, automated retraining

python, Natural Language Processing, Deep Learning, Pytorch, lora, Transformers, langgraph, generative ai, fine tuning, ml evaluations, peft, langchain, embedding, multimodal ai, vector database

Spark, Azure, Python, AWS, Airflow, cloud ML platforms, MLFlow

Databricks, Tensorflow, Pandas, Numpy, MLops, AWS, Pytorch, Python, Azure, Docker, Git, Hugging Face, LLMs, Transformers, MLflow, retrieval-augmented generation, scikit-learn, CI CD, LangChain

S3, PostgreSQL, Tensorflow, Lambda, Javascript, Ec2, Pytorch, Docker, XGBoost, Python, Node.js, Redis, Opencv, FastAPI, MongoDB, Kubernetes, scikit-learn, Hugging Face, TensorRT, TorchScript, Pinecone, ONNX, Stable Diffusion, Detectron2, controlnet, YOLO, AWS SageMaker, Diffusers

Ml, San, Pytorch, Al

containerization , Docker, Asynchronous programming, Python, Kubernetes, LLM agents, cloud platforms, vector databases, gRPC APIs, LLM evaluation frameworks, traditional ML DL models, model serving