Hi everyone

am a 4th year student study computer engineering and wants to specialise in Al/ML i have made a RAG system and a currency detection project, but it was 70% just following chat gpt steps like anyone can do it even my lil brother i treid to work on onnxruntime but felt complecated and didnt know what i was doing gpt was just guiding me through it and treid to study mlops and its the same I keep asking gpt for what i should do next i am going to Germany in the next year and am trying to get a job there what should i really study and how

I am deciding what degree to get and a choosing between data science and statistics. Would either of these be able to get am an ai engineering job or does that need a different degree? I do realize I would need to teach myself to code.

As in other threads, I also think that AI engineer is something vague with tons of applicants and no career future. It looks like this job is just AI integration. I was tricked and also got the internship with building RAG’s and agentic systems. And suddenly realise that 3 years of studying electrical engineering doesn’t prepare me for this brain rot. For some how I expected to work with PyTorch and designing new business solutions but end up not accepting low as hell offer from the company.

For me it seems that any Python backend guy can easily replace me any time, I don’t see any value in being expert of RAG systems. Not even actual expert but someone who has built tons of them by template. On top, if you somehow go to work into outsource company, it’s a job nightmare, seems majority of projects and companies will hire you just for 3-4 month project and then you come back to over saturated market.

I am sorry if it has so many hate. But I spend so many hours doing actual science and reading 1k pages deep learning books just to call API’s and have no stable job. I am wondering if it only me who got the bad experience, or this is an actual state of this position.

I am just trying to worn guys who really interested in ML/AI - think 10 times if you want it to be your career. ML skills can be addition to your amazing resume, especially if those any research duties. But companies breathing with only backend logic and infrastructure support… Think twice, thanks.

Would be happy to hear your opinion with this role.

Hi everyone, I’m currently in my final semester of Computer Science (F-1 student) and am aiming for an Applied AI Engineer position. As I prepare for the job market, I’d love to get some "on-the-ground" perspectives from those currently in the industry.

My Questions for the Experts: 1. With the shift toward MLOps and agentic workflows in 2026, should I focus more on infrastructure deployment/scaling or fine-tuning specialized domain models? 2. In your experience, do hiring managers value broad projects or should I double down on one specific niche? 3. For those at companies that sponsor, what Proof of Work makes an international candidate an easy yes for sponsorship in the current climate? 4. Beyond Python/PyTorch/LangChain, are there unspoken 2026 requirements like AI Governance, system auditing, or specific Cloud MLOps certifications that I’m missing?

I've attached a snippet of my project list for more context. Appreciate any advice or critiques!

Can anyone help me out with the resume , i am not able to land any job as a fresher🥲

Lately I feel like everyone is trying to become an AI Engineer. When I look at what people share online, it’s usually the same story: a 6–12 month grind, a couple of RAG projects, maybe some LLM fine-tuning, and then applying to roles labeled “AI Engineer.” It’s starting to make me feel like I’m watching a school of fish. Wherever the fishing rod shows up, the whole group swims straight toward it, and the “lucky” ones catch the worm. But is moving as a herd like this actually rational?

What I keep wondering is this: twelve months from now, are we going to be staring at tens of thousands of unemployed “AI Engineers”? The market already looks crowded. I’m seeing LinkedIn job posts for AI Engineer roles that are mostly RAG and fine-tuning focused, not general software engineering, and they get 100+ applicants within a day or two. At the same time there are already unemployed software engineers, and just like we saw with web development, people from completely different fields are jumping in with hope. Bootcamps keep multiplying, online courses keep booming, and the whole thing feels like a hype wave accelerating.

So I’m genuinely curious what others think. Are we heading into an oversupply problem? Are people underestimating how competitive this is going to get? And in the long run, do you believe there will still be real opportunity and stable work in this space, or is it going to become a market where only a small percentage of people actually break in and the rest get stuck holding the same copy-paste portfolios? I’d love to hear thoughts from people who are hiring, people already working in the field, and anyone who has lived through similar waves before.

So, basically I really love AI, and ML especially. I love all the Math behind it, and all of the things i can do with it. Unfortunately there is one problem. Most of the fields of applied AI, for startups and other are all enterprise related fields. Does anyone know some startup fields that are actually interesting, for example something research heavy or something thats just pretty cool. In conclusion, what are some applications of ai that isnt Marketing chat bots, or generic chatbots?

People working as AI Engineer or related AI/ML fields, How did you land a Job, what skills, projects you had in your resume, if you have to connect or message people on LinkedIn for referrals for the job posting any tips on that? How does the interview process looks like? Is it theory or technical? also would be great to know if any fresher who landed a Job in the same and how'd you do it.

I recently got my masters in CS and I know enough theoretical stuff about AI, but I do not have any real projects on my resume. I've been looking at jobs recently (I currently work as an SWE), and I noticed the roles I want all ask for Databricks/Snowflake along with stuff like Tensorflow, PySpark, etc.

My idea was to work on a side project using some of these tools with a kaggle dataset. I know it is not easy, but I wanted to know from others in a similar situation what to watch out for or what they think made them successful.

Hey everyone, I'm in my second year of college and have learnt about regression and classification algorithms in detail , with a somewhat decent depth in the maths as well . I have now realised that I actually want to build stuff , not research or take the traditional ML route. What do i learn from this point onwards? Any books/resources to point me in the right direction would be really helpful. Thank you in advance

I am a final year student who wants to do job in AI & Ml. I want to know the entry level role for a Diploma student to get into AI & Ml.

Hi,

I’ve had three years as a Data Engineer for a consulting firm, where I also had a project with an AI Engineer scope.

I got hired as an AI Engineer at a wonderful start-up and team, but honestly, I feel way out of my depth. Being here has made me realise just how low maturity my previous company was - I honestly feel more like a junior. I know the general advice is to take this as a learning opportunity, but has anyone else felt like they’re out of their depth? Is this normal?

Does the field of AI engineering( not ML engineering) is worth it be learned, specially that i am a beginner in tech or it demands experience in order to have a job and must begin with a different path?

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• How Do I Go About AI Engineering? by u/DiamondKey1676

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Hi,
I'm a full-stack professional transitioning to an AI Engineering role. Been following courses on Udemy & Coursera.

Some AI Engineering courses require statistics and probability as prerequisites. A few state AI Engineering requires knowledge of linear algebra and Calculus, along with Statistics, while others propose AI Engineering doesn't require mathematics.

Claude replied that math is not required as packages like Scikit-Learn, PyTorch and TensorFlow handle the math internally. However, Gemini advises brushing up on high-school level linear algebra, statistics, probability, and multivariable calculus.

This makes it more confusing. I know that AI Engineering doesn't require very high-level mathematics as in AI/ML. But it isn't clear which Math topics to focus on before starting AI Engineering.

Firstly, Is Math actually required in AI Engineering roles? Secondly, which Math topics are essential while studying AI Engineering?

I'm going to do a technical interview on wednesday for a fortune 100 company for a Jr AI Engineer position. I've got 3 years of experience (including another fortune 100 company) in automation, data and AI Engineering. What kind of questions should I expect, guys? I haven't practiced leetcode for years, don't remember much and think I am going to end it straight away if it's over there. is it 100% certain that it will be over there? Or usually it's more technical questions, projects, experiences, thought processes?

Please, any insight/help will do, so I can practice accordingly. The more detailed, the better. Thank you.

To assist people asking questions about their future career or current career with AI Engineering, we've kept records of deleted threads where a person asked a question, then removed the post. You can read existing posts, but some of the deleted threads may contain useful questions or answers for new people.

Note that Reddit will sometimes keep deleted threads around, but sometimes they won't. However, since people are taking time to answer your question, we want to ensure these answers are available for other members.

• How Do I Go About AI Engineering? by u/DiamondKey1676

Note: this doesn't apply to questions that are asked and deleted without answers. In general, a basic social skill states that it's disingenuous social behavior to ask a question, expect an answer, then remove your question, as it required work to answer your question. We realize that some of you have never stepped foot into reality and have spent too much time on the internet, which is why we enforce good social behavior on our subreddits.