About

AI/ML engineer, full-stack builder, ex-acoustician.

I’m Mike Fuller. I build production AI systems and consumer AI products, equally at home architecting multi-provider agent pipelines and wiring the Next.js / Supabase stack that ships them.

I came to AI deliberately, mid-career. After a decade as an acoustic consultant (300+ projects UK/NZ and my own acoustic panel and diffusor-manufacturing company in Colombia), I retrained: an MSc in Artificial Intelligence (Distinction) at the University of Bath, with a dissertation on the confidence calibration of foundation language models and an arXiv paper.

Since then: Data Science at Nike across a ~300M-member base, two years of LLM-integrated SaaS, and now co-founding and building brandmodal while building solo products on the side.

I’m a native English speaker, fluent in Spanish, based in Bogotá with full US-Central time-zone overlap.

01/Experience

  1. brandmodal

    Jan 2026 – Present

    Technical Co-Founder

    An early-stage startup building an AI agent team for small businesses' online presence. Two-person founding team.

    Co-founded with Kukesh Kodess.

    • Building the product end-to-end with my cofounder: brand-strategy agents, a Content Studio GenAI pipeline, AI onboarding, and a website builder that produces brand-aligned sites from a single intake.
    • Multi-provider LLM orchestration across Claude, Gemini and OpenAI using the Claude Agent SDK, OpenAI Agents SDK and Vercel AI SDK, with provider failover and structured-output validation.
    • Across the full Next.js App Router + Supabase + FastAPI stack: schema, Postgres RLS, Supabase Auth, Stripe billing, Vercel deployment.

    Next.js · TypeScript · Supabase · Postgres · FastAPI · Claude · Gemini · OpenAI · Vercel · Stripe

  2. buildmodal

    2026 – Present

    Partner & Engineer

    A forward-deployed AI consultancy — a wing of Modal — that I run in partnership with Kukesh Kodess. We embed with a team, find the workflow where AI will actually move a number, and ship the agent or tool that runs it on their own stack.

    • Forward-deployed engineering: a KPI-and-constraint diagnostic to pick the highest-ROI workflow, then designing, building and deploying the agent, model or internal tool into the client's existing stack — one production workflow live before scaling.
    • Hand off with a human review loop, training and a runbook; the client owns the code and the IP.
  3. Launchpad — PropLLM (AI Real-Estate SaaS)

    Apr 2024 – May 2026

    Full-Stack AI Engineer

    2-engineer product team. Product sunset May 2026.

    • Built and shipped an AI image platform for realtors and homeowners — virtual declutter, staging, renovation and AI video walkthroughs — end-to-end to production, with a realtor in early adoption.
    • Designed async generation pipelines integrating Fal.ai, Gemini and Firecrawl with job queuing, result caching and credit-based Stripe billing.
    • Shipped the Next.js + Supabase + Postgres stack front-to-back: auth, multi-tenant data, file storage, image-diffing UI and Vercel deploys.

    Next.js · Supabase · Postgres · Python · Fal.ai · Gemini · Firecrawl · Stripe

  4. Fellowship.ai

    2024 – 2025

    Mentor & Program Lead

    Launchpad's applied-AI fellowship. Returned to run and mentor cohorts after completing the fellowship myself in 2021.

    • Mentored cohorts of fellows through real-world ML/LLM projects end-to-end — problem framing, approach and code review, evals, and shipping a working system — translating production experience into hands-on teaching.
    • Ran the program side: guiding teams, unblocking technical decisions and setting the bar for what 'production-ready' means.
  5. Nike (via Launchpad)

    Nov 2021 – Mar 2025

    Data Scientist — Member Modelling & Marketing Analytics

    • Built LTV models, engagement scoring and member segmentation across Nike's ~300M-member base on PySpark and Databricks.
    • Designed an Engagement Quality Score and affinity-overlap metrics adopted by the Member Modelling team.

    PySpark · Databricks · SQL · Python · AWS (S3, RDS, Lambda, Batch)

  6. Fellowship.ai

    May – Aug 2021

    Data Science Fellow

    • Built a medical computer-vision system for fetal-gender masking in ultrasound imagery (YOLOv5, OpenCV); published on arXiv.
  7. Ondacoustic / BB & RBA Acoustics

    2012 – 2021

    Principal Acoustic Consultant · Founder

    A prior career: 300+ projects across the UK, NZ and Colombia; founded an acoustic-panel manufacturer; built Python tooling for acoustic modelling.

02/Skills

AI / LLM
Claude API · OpenAI API · Gemini · Vercel AI SDK · Claude Agent SDK · OpenAI Agents SDK · RAG · async generation pipelines · prompt & eval design
Machine Learning
PyTorch · PySpark · Databricks · YOLOv5 · OpenCV · LTV / segmentation modelling · foundation-model calibration (MSc)
Backend
Python · FastAPI · Flask · PostgreSQL · Supabase · REST APIs
Frontend
TypeScript · Next.js (App Router) · React · Tailwind · shadcn/ui
Infra & Auth
Vercel · AWS (S3, RDS, Lambda, Batch) · GCP · Supabase Auth · Stripe
Certifications & Languages
Udacity ML Engineer Nanodegree · deeplearning.ai Deep Learning + TensorFlow Developer · English (native) · Spanish (professional)

03/Education

  1. MSc Artificial Intelligence (Distinction)

    2020 – 2023

    University of Bath, UK

    Dissertation: On the Confidence Calibration of Foundation Language Models.

  2. MSc Environmental Acoustics (Merit)

    2010 – 2011

    University of Salford, UK

  3. BSc Engineering & Business Studies (2:1)

    2006 – 2009

    University of Warwick, UK