Tensorflow, Data Science, Pytorch, Python, R, Machine learning frameworks, Cloud platforms

data engineering , Kafka, Python, AWS, Apis, Sql, MLops, Azure, RAG embeddings, anomaly detection, CI CD, LangGraph, Evaluation, event streaming architectures, structured outputs, observability, model monitoring, tool function calling, LLMs, LLMOps, SHAP feature attribution, retrieval evaluation, vector hybrid search, Classification, Semantic Kernel, prompt engineering, agentic workflows, Regression, Applied AI ML, gradient-boosting techniques, LlamaIndex

Python – Expert level SQL – Strong Machine Learning Search & Information Retrieval Recommendation Systems Personalization Ranking / Learning-to-Rank Embeddings Vector Search – FAISS, etc. Hybrid Search – lexical + semantic search Reranking Production ML / MLOps ML Model Deployment & Serving Model Monitoring & Reliability Spark or equivalent Airflow / Dagster or equivalent A/B Testing & Experimentation Offline ML Evaluation, HNSW, pgvector

BigQuery, Gcp, FastAPI, LangChain, Async Python patterns, pgvector, Claude, Pinecone, LangSmith, LangGraph, OpenAI APIs, Vertex AI, AI LLM Engineering, vector DBs, Ragas, Gemini, Weaviate

Cloud Computing, Machine Learning, Data Visualization, Big Data, Python, Sql, Statistical Analysis, Deep Learning

Sql, Nosql, Tensorflow, Numpy, Nlp, Computer Vision, Pandas, Gcp, Pytorch, Keras, Azure, Python, AWS, generative AI, Scikit-learn, ML Ops

Tensorflow, Pytorch, Gcp, MLops, Docker, Azure, Kubernetes, Python, AWS, LangChain, Generative AI, LLaMA, Scikit-learn, Pinecone, GPT, FAISS, LoRA, Weaviate, QLoRA, LlamaIndex, Large Language Models