Founder · Director · Operating Executive
Michael Zeligs, MST
Director and Fractional CMO for founder-led brands — and a Stanford-trained AI research engineer who builds the systems behind the work. Fifteen years turning early companies into fundable, on-camera stories.
For brands & founders
Director & Fractional CMO
Directs flagship brand films and product campaigns, and runs the full launch stack a company needs before it has a CMO — web, video, GTM messaging, customer acquisition, CRO, and the fundraising narrative.
Apple · Amazon · Google · Smithsonian · 100+ founder-led startups.
For AI/ML labs & boards
CXO & AI Research Engineer
Trains and evaluates frontier models on complex executive-decision work, designs the rubrics and harnesses that make that signal reliable, and ships the Python tooling himself.
GDPval-style benchmarking · occupational-complexity evals · RLHF program design.
On a shoot, Michael directs. Off it, he writes the Python, designs the funnel, and edits the cut. The point of a boutique is that the person who sets the vision is the person who ships it — no hand-offs, no dilution.
Frontier AI, in practice
The reason labs hire a real operator to grade models: judgment is the bottleneck, not labeling. Michael encodes senior business expertise into training signal — then builds the tooling that makes it scale.
GDPval
Benchmarks frontier models against real, economically valuable knowledge work — authoring tasks and rubrics drawn from how executives actually spend their day.
30 hrs → minutes
Decomposes high-complexity occupational tasks — the kind that take a CEO 30 hours by hand — into structured evaluations a model can be trained and graded against.
45 → 8 min
Built the Python evaluation harness that cut per-task review from 45 to 8 minutes and tripled cohort throughput.
Operating executive and hands-on engineer with fifteen years building and scaling technology companies from zero through institutional fundraises, paired with marketing and communications leadership that has influenced $400M+ in client funding and revenue. Stanford-trained in computational engineering and digital signal processing at CCRMA — the Center for Computer Research in Music and Acoustics.
Currently a Senior AI Research Engineer at Project Horizon — Spectra Division (Diamond Fellowship · Prodigy Cohort), and CTO & CEO of ApertureAPI, an API-first platform for AI/ML systems integration accepted into Stanford StartX.
Prior leadership: Director of Engineering Operations at Clockwork AI (built the technical narrative behind a $100M+ Series A); engineering and marketing lead on the Apple Green Bond–backed Radian Solar Project across Terabase Energy and Intersect Power; and Technical Program Manager at Amazon Advertising on Fire TV streaming ads serving 50M+ monthly users.
Selected clients & campaigns
Amazon Advertising (Fire TV) · Google · Kleiner Perkins · Terabase Energy · Intersect Power · Baubax · Konnected · HDS Global · Sutter Health · Airbus · Tap Systems · Foldio · Zipbuds · Smithsonian · Discovery Channel.
Client launches featured on CNN Money · TODAY · Ellen
Selected work & engagements
Range
The director, the designer, the engineer, and the musician are the same person — which is why the work holds together.
Design
Brand systems, web layout, and campaign art direction — the visual layer that makes a young company look fundable.
Music & sound
Composition and signal processing from Stanford CCRMA — scoring, sound design, and the acoustics research behind two patents.
Engineering
Production Python, C++, and JavaScript daily — automation, data pipelines, and the evaluation tooling behind the AI work.
Patents & publications
- Telecommunications patent — an impedance-matched, mechanically tunable, self-resonant quadrafilar helical phased array for low-power Tx-Rx across OTH radar, UHF near-space, and X-band deep-space regimes.
- Signal-processing patent — a cubic conversion method for bidirectional mapping between electromagnetic and acoustic spectra.
- Published researcher in video engineering and digital signal processing, with Stanford CCRMA collaborations.
Education
Stanford University — CCRMA. B.A. in Media, Science & Technology (MST): video engineering and digital signal processing at the Center for Computer Research in Music and Acoustics. DSP, parallel and real-time systems, filter and codec design, software synthesis in C++/Python/JS, with foundations in linear algebra, Fourier analysis, and optimization.
Honors
- Diamond Fellowship · Project Horizon
- Prodigy Cohort · Gather Platform
- Stanford StartX · ApertureAPI
- Stanford Creativity in the Arts
- Rotary Youth Leadership Award
Two ways to work together
Start a video project
Hire Michael (CMO / AI)
Petaluma, California · mzeligs@alumni.stanford.edu · Download CV (PDF)