Machine Learning Operations, Data preprocessing and feature engineering techniques, Cloud-based AI services

workflow engines , Python, tool function calling, tracing observability tooling, Logfire, AI systems in production, prompting, Temporal, OpenTelemetry, pydantic-ai, LiteLLM, MCP, agent architectures

Apis, Performance Monitoring, Version Control, Gcp, MLops, Azure, Python, Statistical Analysis, Machine Learning Algorithms, AWS, data preprocessing, cloud platforms, production-ready ML pipelines, model evaluation, deep learning techniques, feature engineering, model lifecycle management, model optimization, hyperparameter tuning

AWS EKS, FastAPI, Kubernetes, Python, Celery, Sqlalchemy, Airflow, Claude API, confidence calibration techniques, Pydantic, LLM output validation frameworks, embedding models, Weaviate, pgvector, Pinecone, semantic search, RAG context

triton , Pytorch, Kubernetes, Python, Docker, Qdrant, vLLM, LlamaIndex, Airflow, Weaviate, pgvector, LangChain, TGI, CrewAI, Pinecone, LangGraph, GPTQ, MLOps tools, Kubeflow, MLflow, quantization techniques, Scikit-learn, AWQ, Hugging Face ecosystem, AutoGen, GGUF, Weights Biases, FAISS

data engineering , Ml, FastAPI, Kubernetes, Python, AWS EKS, Nlp, Celery, Sqlalchemy, confidence calibration techniques, Airflow, Claude API, vector database, Ai, Pydantic, LLM output validation frameworks, embedding models, Weaviate, pgvector, semantic search, data ingestion pipelines, Pinecone, LLM evaluation frameworks, prompt engineering

amazon sqs , snowflake , Databricks, Sql, Rabbitmq, New Relic, Golang, Grafana, Postgres, Numpy, AWS, Restful Services, Cassandra, Tensorflow, Python, Nosql, GenAI, ScikitLearn, NLP libraries, Apache Kafka MSK, Agentic AI, MLlib

Data Science, Python, LangGraph, Statistical Modeling, Agentic Workflows using LangChain-based agents, Transformer architecture, Fine-tuning techniques for LLMs