A tier-3 college final-year ISE student with ongoing ML research publications (TMLR, NeurIPS targets) seeks advice on the practical value of research credentials for industry jobs in India and higher studies abroad, versus traditional DSA/dev focus.
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.
A software engineer with 40+ years and staff-level experience seeks advice on transitioning to a research engineer role, discussing the realistic prospects, required experience, and strategy options given their strong technical background but limited recent applied ML work.
A software engineering student seeks final-year project ideas that combine AI/ML and cloud computing to solve real-world problems and boost employability.
A PhD graduate asks whether publishing exclusively in peer-reviewed journals (TMLR, JMLR, Neurocomputing) instead of top ML conferences (NeurIPS, ICML) would negatively impact their chances of landing industry research scientist positions.