# Is ML Experience A Liability For AI Engineering?

DevFeed: [Is ML Experience A Liability For AI Engineering?](<https://devfeed.tech/articles/is-ml-experience-a-liability-for-ai-engineering-33447.md>)

Original publisher: [Read original article](<https://timkellogg.me/blog/2024/12/10/ml-liability>)

Published: 2024-12-10T00:00:00Z

Content type: opinion

Language: en

Sources: [Tim Kellogg](<https://devfeed.tech/sources/tim-kellogg.md>)

Topics: [AI Engineering](<https://devfeed.tech/topics/ai-engineering.md>), [Machine learning](<https://devfeed.tech/topics/machine-learning.md>), [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>), [Large Language Model](<https://devfeed.tech/topics/llm.md>), [Data Science](<https://devfeed.tech/topics/data-science.md>)

Tags: [ai](<https://devfeed.tech/tags/ai.md>), [ai-engineer](<https://devfeed.tech/tags/ai-engineer.md>), [ai-engineering](<https://devfeed.tech/tags/ai-engineering.md>), [fine-tuning](<https://devfeed.tech/tags/fine-tuning.md>), [llm](<https://devfeed.tech/tags/llm.md>), [ml](<https://devfeed.tech/tags/ml.md>)

## AI overview

An opinion article examines whether prior machine learning experience can hinder a transition into AI engineering. It presents a more balanced view, describing data-pipeline, UX, and model-centric archetypes and contrasting their approaches to LLMs, fine-tuning, model complexity, and engineering tradeoffs.

## Source excerpt

Yesterday I posted here about becoming an AI Engineer and made a statement that prior ML experience is often a liability for transitioning into AI engineering. That turned out to be quite the hot take! In this post I'll incorporate feedback and try to expand that into a more balanced take. I'll expand on the perspective of it being an asset, as well as where it's a liability.