Andy Sarroff
Head of Applied Ai @Native Instruments
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WORK HISTORY
Head of Applied Ai @Native Instruments
Boston, MA, US
Lead a hub-and-spoke Applied AI organization (engineers embedded in product teams) across Native Instruments and iZotope; allocate headcount and compute to the highest-leverage bets while PMs retain ship decisions.• Enable product teams to ship ML/DSP capabilities across flagship products (Guitar Rig, Ozone, Nectar, RX, Traktor, Absynth).• Lead incubation through public alpha for Kompanion (transformer language frontend + neural audio codec), including acceptance criteria, unit economics criteria, and usage-driven go/no-go decisions.• Partner with Legal and Business Development on data rights and partnering decisions: define data-use approval paths, vendor data terms, validation benchmarks, unit economics, and integration readiness criteria.• People leadership: built and developed a lean, high-performing Applied AI team; coached and promoted talent.
EDUCATION
Wesleyan University
BA, Music
Dartmouth College
Doctor of Philosophy - PhD, Computer Science
New York University
Master of Music (MM), Music Technology
ABOUT ANDY SARROFF
Applied AI leader in creator tools with 15+ years building and shipping audio ML/DSP products. I lead a hub-and-spoke Applied AI organization (engineers embedded in product teams) and drive outcomes through portfolio investment choices (headcount + compute), cross-functional alignment, and pragmatic standards that make ML/DSP shippable.What I do• Lead a hub-and-spoke Applied AI org across product teams; align Product/Design/Engineering so ML/DSP work lands as shippable capabilities.• Allocate headcount and compute to the highest-leverage product bets while PMs retain ship decisions.• Set practical AI standards/guardrails so teams can move fast without rework.• Partner with Legal and Business Development on data rights and partnering decisions; define vendor data terms, validation benchmarks, unit economics gates, and integration readiness criteria.Selected proof points• Shipped ML/DSP capabilities across flagship products (Guitar Rig, Ozone, Nectar, RX, Traktor, Absynth), working directly with product teams to land research as production features.• Led incubation through public alpha for Kompanion (transformer language frontend + neural audio codec), including acceptance criteria, unit economics criteria, and usage-driven go/no-go decisions.• People leadership: built and developed a lean, high-performing Applied AI team; coached and promoted talent.I work at the intersection of ML, DSP, and product engineering to make creator-facing intelligence practical, reliable, and shippable.
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