#AMD vs NASA Pathways

1 messages · Page 1 of 1 (latest)

dense trail
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Already accepted AMD summer 2026 because NASA said January start date was final and I didn’t wanna take spring off from school. However now they want me for summer apparently. Worth renege?

AMD:
Austin, TX
42hr
CPU Specialist Engineering team, C++
Cool team, good xp.
Already worked at Intel last year so a lot of chip companies

NASA:
Edwards airbase, CA
Around 30hr?
Putting AI in compilers/FPGAs
Work on the base, cool planes all around.
Apparently Pathways program more prestigious than OSTEM program?

halcyon dust
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AMD

wintry zealot
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Just go AMD

terse cairn
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you interned at intel GPU as a freshman? and deciding between AMD and NASA pathways as sophomore? man, you are cracked

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one quirk with nasa is you will need 480 hrs (12 wks) to be considered for conversion. nasa summer is normally 10 wks

limpid mural
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amd

dense trail
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I put sophomore because I’m graduating 2028, I need an extra semester bc I took 1 off

limpid mural
dense trail
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Yeah

limpid mural
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ok cool

dense trail
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Oh fire how is it

limpid mural
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havent gotten there yet lol

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start next week

terse cairn
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if you are debating this, it indicates you are not pursuing semiconductor industry or NASA. correct?

dense trail
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Nope it’s the bones I’ve been thrown, i still dk what to do with my life

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Besides that I like tech

terse cairn
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if you want to pursue semiconductor, then AMD.
if you want aerospace/defense/nasa, then nasa.

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saw you go to tech compe. i think pigeonholing semiconductor is worth the risk here

dense trail
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Yeah I’m not worried about pigeonholing, I’m 20 lol

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Could start life over twice and still not be 30

slender night
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Do you want to eventually working in the edge ML space? That's the only reason I see you taking nasa

terse cairn
slender night
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I don't work there

terse cairn
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afaik, AFRC doesn't

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if he chooses NASA AFRC, he will likely work on X-59 project

slender night
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acc. to op's initial post, he would be doing ai compiler work or deploying models on fpgas (which is not traditional ml work) but would fit pretty great into edge ml applications

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which is more tied to hardware/software codesign which could be very interesting to op