Ep21: From Zero to GenAI - What ML Engineers & Data Scientists Need to Learn

How is AI quietly reshaping your everyday workflow—whether you notice it or not? In this episode of the Data Neighbor Podcast, we explore how AI is being embedded directly into the tools you already use, with real-world examples from Adobe Acrobat.Our guest, Nikhil Pentapalli, is a Senior Machine Learning Engineer at Adobe, where he works on embedding GenAI into Acrobat to transform how people interact with documents. From AI assistants that can summarize and answer questions across multiple PDFs, to intelligent restructuring of scanned documents for mobile, we unpack what it really looks like to bring AI into production—and why it’s harder than it seems.We cover:- How AI is becoming invisible infrastructure in everyday workflows. - Why integrating AI into documents is harder than you'd think. - What makes PDFs complex, and how GenAI is making them smarter. - Building GenAI products: from prompt engineering to memory optimization. - Advice for breaking into GenAI, and what ML engineers need to know now. - Traditional ML vs LLMs: where to use which, and how to manage costs.Whether you're building AI tools, thinking about career moves, or just curious about what it takes to ship real GenAI products, this episode is loaded with insights and practical advice.Connect with Hai, Sravya, and Shane:- Hai: https://www.linkedin.com/in/hai-guan-6b58a7a/- Sravya: https://www.linkedin.com/in/sravyamadipalli/- Shane: https://www.linkedin.com/in/shaneausleybutler/#genai #aiworkflow #documentai #rag #retrievalaugmentedgeneration #acrobatai #llm #promptengineering #mlengineer #aiintegration #realworldai #aiproducts #datascience #dataneighborpodcast

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