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franciscomnroy

Francisco M.

@franciscomnroy

iOS and ML Engineer

Vereinigte Staaten
Englisch
Einige Informationen werden in englischer Sprache angezeigt.
Über mich
I'm a self-taught iOS developer who builds consumer apps end to end, from initial design to App Store submission to paid ads and organic marketing. I think like a founder, not just an engineer. That means I care about why we're building something. I've 5 published apps with 15k+ downloads across the full stack: Swift on the frontend, Firebase and Python Cloud Functions on the backend, RevenueCat for monetization, and organic TikTok and Instagram content for growth. I document architecture decisions, write tests, and structure code that's maintainable, not just AI code that works today.... Mehr lesen

Kompetenzen

f
franciscomnroy
Francisco M.
offline • 

Meine Dienstleistungen

iOS-App-Entwicklung
I will develop your ios app from design to app store submission

Portfolio

Arbeitserfahrung

NVIDIA

NVIDIA

Vollzeit • 9 mos

ASIC Physical Design Intern

Jun 2022 - Dec 20226 mos

As a returning ASIC PD intern at NVIDIA, I was given an open-ended internship. I was responsible for exploring and implementing power-saving techniques for NVIDIA’s GPU chips. I conducted a thorough literature review and developed novel methods to obtain insights into a chip’s power consumption to assess the effectiveness of various techniques. These methods opened up new possibilities for exploration and improvement that was not previously possible. I presented these findings internally at NVIDIA, including at interdisciplinary team meetings and an intern poster presentation competition, to share my work and gather feedback. In addition, I also presented my previous internship work at NVIDIA’s NTECH conference, which is a highly competitive internal conference with an acceptance rate of less than 20%.

ASIC Physical Design Intern

Jun 2021 - Sep 20213 mos

As an ASIC PD intern at NVIDIA, I contributed to the development and integration of a power-saving technique to make it standard for NVIDIA's GPU chips. I also presented this technique internally at NVIDIA, including at interdisciplinary team meetings, to share my work and gather feedback.