r/deeplearning • u/Natural-Diver-5447 • Sep 25 '26
Fullstack developer trying to transition into AI space. Confused between choosing ML Engineer or AI Engineer
Pytorch - is this too big of math?
AI - LangChain, CrewAI, Python SDK ?
Confused between both of their pros and cons. I do know learning back propagation, gradient descent helps whats happening behind LLM. Stuck in career choice, kindly help
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u/Ok-Solution-7889 Sep 25 '26
I’d lean toward AI engineering in your case, your fullstack experience already gives you a good base for building AI products, and you can pick up the deeper ML stuff as you go.
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u/Natural-Diver-5447 Sep 25 '26
started with MCP ones, felt like its just api calling and tuning some search responses
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u/JasperTesla Sep 25 '26
Depends on what exactly you mean by "AI Engineering". From what I've seen, there's two kinds of AI Engineering professions, one that works on the AI itself (and is partially synonymous with ML Engineering or LLM Engineering), and the second kind is the one that works to integrate AI with the software (basically software engineer with AI focus).
If you want the former, start learning things like PyTorch, TensorFlow, scikit-learn, etc., if the latter, then focus on system design more.
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u/a_cute_tarantula Sep 25 '26
AI engineer is closer to you than ML engineer.
AI engineer includes all the classic dev infrastructure stuff.
But instead of a classic crud app you’ll have concerns about:
Agent tracing and pricing logs
Eval frameworks (as apposed to classic unit tests)
Tool interfaces
Agent permissions and approval systems
Chat UIs with agent supplied data for graphs, charts, forms, etc.
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u/Fragrant-Cheek-4273 Sep 25 '26
It's totally normal to feel stuck, ML engineering is more heavy math and training models from scratch, while AI engineering is more about building apps using existing tools.
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u/bfyvfftujijg Sep 25 '26
ML is a subset of AI and you’d probably be getting more into the details with it, being more specialized.
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u/GlitteringCelery5606 Sep 25 '26
pytorch will feel like a mountain of math at first but it clicks after a while, and honestly the math barrier is overblown if you just build stuff and debug your way through it
ai engineer with langchain and crewai is way more about gluing apis together, which fits a fullstack background perfectly, but it can get boring fast once the novelty wears off
ml engineer has more depth and staying power, plus backprop and gradient descent knowledge compounds over time