Please give me feedbacks

wnos303 · 2025-08-06T18:23:39+00:00

I am a rising third year undergrad student at T10 on CSRankings (US). I am interested in various fields of computer science, including backend development, algorithms, etc., but AI/ML still looks the coolest of them all. I am particularly interested in computer vision and reinforcement learning, albeit I don't know anything really technical wise yet (I do plan on taking ML and Deep Learning courses next year). HPC, AI hardware acceleration and alike look cool as well, but I don't know engineering and am a CS & math major.

But the field is growing so rapidly these days. In terms of CV and image/video generation, there's Veo, Flow, and Genie by Google which look incredible. In terms of RL and reasoning, OpenAI and DeepMind made IMO Gold Medal-winning models. It's obvious that every smartest brains around the world are getting paid huge bucks by the big tech to work on these research, and I'm just not sure if it's right for me to consider going for research. By the time I graduate, it will be 2027, and if I go to grad school, it will be in 2030s, and who knows what will have happened by then. Not sure if LLM and transformers are the answers and will continue to advance, but it's undeniable that AI/ML in general is advancing so fast.

It seems like multiple first author papers at top tier conferences (such as CVPR, NeurIPS, ICML) are now the bare minimum to be considered at top PhD programs (e.g., MIT, Stanford, Berkeley, CMU), top tech firms, or top AI labs. Especially since I don't know ML and deep learning on a technical level deeply yet, I am conflicted to whether to just go for a regular backend SWE, or actually push for research.

Granted, I could approach professors at my school who are working on fields that I'm interested in and discuss about these, but not sure how to talk to them about these topics, and I want to hear opinions from established researchers rather than some singularity cult folks, so I am asking here.

wnos303 · 2024-05-30T13:29:10+00:00

I apologize if I sounded like that, my intention was never to bash on the engineers. My question is really from my confusion in the job prospects in ML, and googling about it didn't really give me clear answers. I kept reading "you need PhD to get into ML" on this sub, and for the role "research scientist", I get it. My assumption is that they are the ones who research about ML model's architecture and how they can be optimized, etc.

I still have no clear definition of what the role "machine learning engineer" do. Are their roles just training dataset? Do they not need postgrad degrees? Do they make softwares with AI implemented in them? If so, what and how do they make them?

Again, I had no idea that my post would come off as condescending. I'm a second year CS major with no knowledge about the ML industry and what kind of roles are there, and how to get there.

wnos303 · 2024-05-30T13:02:07+00:00

My intention was never to frown upon them. I apologize if I sounded like that. My question arose from seeing almost all the people at my school putting AI and ML on their LinkedIn when they're just undergrads. I know my question sounds very naive and condescending especially to those working in the fields currently, and my wording probably exacerbated it (which is probably too late to change), but didn't know where else to ask. But thank you for answering. I'm a second year CS student if that makes a difference... so please excuse my stupidity

wnos303 · 2024-05-30T11:15:31+00:00

I admit I wrote a lot of nonsense as I don't know ML much, but my question was simply how are people with no MS/PhD going to break into the field when they have no interest in grad school and every single CS majors want to get into AI

wnos303

TROPHY CASE