Job Description
Job description
REQUIREMENTS:
Total experience of 6 years+
Strong expertise in Python and backend engineering with experience building scalable, distributed microservices.
Hands-on experience designing and delivering end-to-end RAG (Retrieval-Augmented Generation) workflows in production systems.
Solid understanding of ML solution design, including embeddings, retrieval, ranking, feature engineering, and evaluation strategies.
Experience with vector databases (FAISS, Pinecone, Milvus, Weaviate) and implementing chunking, indexing, vector search, re-ranking, caching, and memory patterns.
Knowledge of LLM/NLP engineering, including prompt engineering, model integration, orchestration tools (Lang Chain/Llama Index), and evaluation instrumentation.
Experience productionizing ML systems with observability, online/offline parity, and performance optimization across latency, throughput, and cost.
Strong backend integration skills using REST/g RPC APIs, Docker, Kuber...
REQUIREMENTS:
Total experience of 6 years+
Strong expertise in Python and backend engineering with experience building scalable, distributed microservices.
Hands-on experience designing and delivering end-to-end RAG (Retrieval-Augmented Generation) workflows in production systems.
Solid understanding of ML solution design, including embeddings, retrieval, ranking, feature engineering, and evaluation strategies.
Experience with vector databases (FAISS, Pinecone, Milvus, Weaviate) and implementing chunking, indexing, vector search, re-ranking, caching, and memory patterns.
Knowledge of LLM/NLP engineering, including prompt engineering, model integration, orchestration tools (Lang Chain/Llama Index), and evaluation instrumentation.
Experience productionizing ML systems with observability, online/offline parity, and performance optimization across latency, throughput, and cost.
Strong backend integration skills using REST/g RPC APIs, Docker, Kuber...
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