Job Description
MLOps
Retrieval-Augmented Generation (RAG)
JD
8-10 years of relevant experience in Apps Development or systems analysis role
Core AI/ML Foundations:
Strong foundational knowledge in GenAI , Machine Learning (ML modeling), Data Science, Statistics, and AI fundamentals, including Natural Language Processing (NLP), Neural Networks, and Large Language Models (LLMs).
Generative AI & LLM Expertise:
Extensive hands‑on experience
with leading LLMs such as Google Gemini, OpenAI models, Anthropic Claude, Mistral, Llama, and various other open-source LLMs.
Critical:
Deep working knowledge and hands‑on experience with Retrieval‑Augmented Generation (RAG) pipelines, including advanced RAG techniques and their detailed implementation.
Proven ability to build, tune, and deploy LLM‑based applications using platforms like Vertex AI, Hugging Face, etc.
Expertise in developing robust prompt enginee...
Retrieval-Augmented Generation (RAG)
JD
8-10 years of relevant experience in Apps Development or systems analysis role
Core AI/ML Foundations:
Strong foundational knowledge in GenAI , Machine Learning (ML modeling), Data Science, Statistics, and AI fundamentals, including Natural Language Processing (NLP), Neural Networks, and Large Language Models (LLMs).
Generative AI & LLM Expertise:
Extensive hands‑on experience
with leading LLMs such as Google Gemini, OpenAI models, Anthropic Claude, Mistral, Llama, and various other open-source LLMs.
Critical:
Deep working knowledge and hands‑on experience with Retrieval‑Augmented Generation (RAG) pipelines, including advanced RAG techniques and their detailed implementation.
Proven ability to build, tune, and deploy LLM‑based applications using platforms like Vertex AI, Hugging Face, etc.
Expertise in developing robust prompt enginee...
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