I went through a bunch of older posts here about research vs dev roles, but most of them were either very general or not really in a similar situation, so posting this.
I’m a final year ISE student from a tier-3 college. Over the past 1.5–2 years I’ve been focusing quite a bit on ML research instead of just the usual DSA + dev route.
Current situation:
- 1 paper in TMLR (reviews done, waiting on decision)
- 1 in Data Science and Management (under review)
- 1 planned for IEEE Access
- 1 I’m trying for NeurIPS main track (I know this one’s a long shot)
- 2 month internship at Accenture in 3rd year
- Some ML projects apart from the research work
I know not everything will land. But assuming a realistic outcome where maybe 1–2 of these get accepted at a decent level (Q1/A* types), I’m trying to figure out what that actually changes.
A few things I’m confused about:
For jobs in India:
Does this actually help with shortlisting for ML/SDE roles, or after a point does it not matter much and it just comes down to DSA + interviews anyway?
Also, being from a tier-3 college, does this help offset that at all? Or do companies still filter heavily based on college first?
For higher studies:
Does having papers like this make a noticeable difference for MS/PhD abroad (US/EU), or is it just a “nice to have”?
Do colleges really care about the difference between something like NeurIPS vs a Q1 journal vs IEEE Access, or is it all seen more or less similarly?
And one thing I’m seriously unsure about:
If I’m leaning towards industry (ML/AI roles), is continuing research actually worth the time, or would that effort be better spent on DSA, systems, etc?
Also, is it even realistic to aim for roles like research engineer / research scientist from this background, or should I treat that as a long-term thing (like after M.tech/PhD)?
Would prefer honest answers over motivational ones. Trying to decide how to spend the next few months properly.
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