Is a second MSc worth it? [D]
Mirrored from r/MachineLearning for archival readability. Support the source by reading on the original site.
I’m an AI research engineer based in Africa with about 3 YoEs in RL, LLMs, post-training, and systems efficiency (CUDA/vLLM). However, on a smaller scale because of compute limits. My undergrad and Master’s are both in communications engineering. I did a 5th-year Master's at my local university while working full-time at a telecom company, focusing on RL in telecom. Publication-wise, I have one paper published in a peer-reviewed mid-tier AI/telecom conference, a patent, and another paper that was accepted but never published because we couldn't fund it.
Over the past year, I’ve hit the below walls:
PhD Applications (~10 mid-tier labs): Rejected by all. I read their recent papers, put together proposal ideas, and reached out to PIs, but didn't get traction.
Research Engineer Roles (~100 applications): Applied directly, reached out to engineers in similar roles for resume reviews or referrals, but didn't pass a single initial screening.
Cold Emails for Internships (~400 sent): I read labs' papers, asked targeted questions, and chatted with authors. They’d often be interested in the technical ideas, but as soon as I brought up doing an internship, I almost always got ghosted (got 3 actual replies, all saying no capacity).
I’m starting to think the location and university brand are major bottlenecks, so I'm considering doing a second CS Master’s abroad to get my foot in the door. But I really don't want to spend two years going in the wrong direction if there's a better way.
What other paths or changes would you suggest?
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