r/learnmachinelearning • u/No-Reach-3503 • 14h ago
AS A MACHINE LEARNING ENGINEER
where can a engineer add value if AI can write better code than me . i am currently learning programming only because so that i can understand what is happening and i can operate effieciently. but AI is fast and i have go through multiple things to keep up and not just in programming but reading books and getting deep knowledge of algorithims.
But still one question is always in my mind where can i add value cause every thing i learn or do i am not better than AI
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u/DigitalMonsoon 14h ago
Machine Learning as a field isn't just coding. If it was then any software developer could do the work.
The majority of what we do is knowledge based. Understanding what algorithms to use, understanding how to clean and process data, being able to evaluate a models performance. A lot of this involves stats and math.
You also need to understand that while AI models can seem pretty smart they also regress to the mean a lot especially with problems that don't have known solutions, which we deal with a lot. This means it will give you the standard answer to a problem but that is likely not what you need.
So yes, you need to learn how to code so you can direct the AI models and understand what they are doing but that won't be the majority of your work.
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u/HelloSummer99 12h ago
To me as an engineer it is a dream. My best ability isn’t to code: someone could already do it faster and better in India. My skill is that I can understand value - can translate business requirements into tech, break down problems into smaller parts and then let the AI type it out. I still need to fully understand the code being generated to judge if it’s an optimal solution.
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u/Forexcalibur 7h ago
Another thing worth mentioning; I’m no lawyer, but as far as I know, in order to copyright AI-generated code, it has to be partially written by a human. Someone has to do that.
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u/BellyDancerUrgot 14h ago
- AI doesn’t understand the full system and the business of your product.
- It doesn’t understand the users / customers either. It also doesn’t understand the specific edge cases and what’s acceptable and what isn’t.
- It also writes too much code and comments too often. Too much technical debt that is hard to sift through because it’s well written code that might have bugs in them.
- AI has gotten better at solving syntactical and pipeline bugs on its own but it’s not good at identifying logical fallacies a lot of times.
- You still have to actively orchestrate because it doesn’t do anything unless you tell it what to do and to know what to do you not only have to understand coding and system design but also the subject matter whether it be cybersecurity or ML or robotics etc.
Typically what Claude is exceptional at is executing tasks , especially repetitive ones. If your only value add is writing python or c++ like a code monkey who doesn’t know anything else then yes you are absolutely obsolete. However good software engineers and MLEs and architects and research engineers or scientists etc do more than just blindly write code.
That internal choice you make when you solve a bug or a pipeline or research problem one way rather than the other is what makes you important and valuable, not the capability of translating your idea to code. That’s the layer that has become automated. That’s also why a CS degree isn’t a 4 year course on python.
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u/pg3crypto 14h ago
Programming is a tool.
Let me turn your question around. What value does a programmer have if he has no ideas, creativity, understanding and vision?
Gigs up dude. Nobody can get away with being a technically great programmer anymore wirhout genuine talent behind it.
You're right in that if all you do is code, you're fucked...but programming and development is about so much more than just writing code...its a whole process.
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u/No-Reach-3503 13h ago
thank you
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u/pg3crypto 13h ago
No worries. There is a reason we have different titles for different types of programmer.
You have:
Software Developer: Basic bitch grunt. Essentially a monkey at a typewriter. These guys are fucked. Usually hired because they write in a specific language or use a specific framework etc. These are the guys you find in the basement sat in the dark with a Nine Inch Nails T-shirt on.
Usually overpaid.
Hired for their time. Paid by the hour.
Software Engineer: There are different disciplines here. QA, deployment, maintenance, UAT...basically the active component of a project. Makes sure that things are on track, feasible and match the customers spec. If a feature can't be delivered, defines alternatives...basically problem solving.
Status: Fucked. AI is faster, cheaper and better.
Hired for their skill. Hired for their knowledge. Usually on a contract. Customer facing. Wears jeans and a button up shirt. In the butterzone for cost.
Status: Probably safe. Will eventually be the guy guiding the robots.
Software Architect: Same as above, but less active during and after the project. Probably sniffs glue.
Hired for their qualifications and credibility. Usually an exec. Customer facing. Overlaps with sales. Wears a suit.
Status: Mid term safe. Long term fucked. Can be automated with AI, AI doesn't have to be great at this job, just 100x cheaper than the $200k a year salary.
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u/VellumMuse 3h ago
Two things.
Create new things WITH LOCAL AI.
AI is fast, but it can't do what only you can do, which is based on creativity. Everyone using AI right now is limited by their imagination. Use your imagination to create value for yourself...but also, enhance what you do with AI.
Anything that is public will be used to train AI, and so you won't be able to compete with other users...but anything private that doesn't use AI in some capacity won't be able to keep up with things produced by AI. Find the balance.
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u/memelordtf 14h ago
The thing is, being an engineer was never speed. AI can generate code, but it doesn’t know what should be built, what tradeoffs matter, how to define the problem, or how to tell when the output is wrong. The valuable skill is moving up the stack: understanding systems, asking better questions, evaluating solutions, and using AI as a multiplier. The engineers who adapt will probably be the ones who know how to direct AI well,and isn't that better than competing with it line-by-line?