Gene Grimaldi
Also known asThe Machine
OriginCalifornia
Occupation(s)Mastering engineer
Years active1990s–present

Gene Grimaldi is an American mastering engineer currently operating as chief engineer at Oasis Mastering. He is a two-time Grammy Award for Album of the Year nominee for his mastering duties for Lady Gaga's The Fame and The Fame Monster, as well as a winner of Latin Grammy Award for Record of the Year for Alejandro Sanz and Camila Cabello song "Mi Persona Favorita".

Gene "The Machine" Grimaldi grew up in Pennsylvania and attended Institute of Audio Research in New York City. He used to work as a live sound engineer around the Philadelphia area and then started working at the CBS Records/Sony Music manufacturing facility in Pitman, New Jersey in 1986. He went to Los Angeles to work at Future Disc Systems as a production engineer in 1991. Since late-90s, he started working at Eddy Schreyer's Oasis Mastering as mastering engineer.[1]

Awards and nominations

Grammy Awards
Year Nominee / work Award Result Ref.
2011 The Fame Monster Grammy Award for Album of the Year Nominated [2]
2010 The Fame Nominated
Latin Grammy Awards
Year Nominee / work Award Result Ref.
2022 Dharma Latin Grammy Award for Album of the Year Nominated [3]
2021 Vértigo Nominated
"Si Hubieras Querido" Latin Grammy Award for Record of the Year Nominated
"Un Amor Eterno (Versión Balada)" Nominated
2020 Mesa Para Dos Latin Grammy Award for Album of the Year Nominated
"Lo Que En Ti Veo" Latin Grammy Award for Record of the Year Nominated
2019 #Eldisco Latin Grammy Award for Album of the Year Nominated
"Mi Persona Favorita" Latin Grammy Award for Record of the Year Won
"No Tengo Nada" Nominated
2017 "Vente Pa' Ca" Nominated

References

  1. "Engineer | Oasis Mastering". Oasis Mastering. Retrieved September 6, 2023.
  2. "Gene Grimaldi | Artist | GRAMMY.com". www.grammy.com. Retrieved September 6, 2023.
  3. "Gene Grimaldi | Artist | LatinGRAMMY.com". www.latingrammy.com. Retrieved September 6, 2023.
This article is issued from Wikipedia. The text is licensed under Creative Commons - Attribution - Sharealike. Additional terms may apply for the media files.