Role: Founding CTO – Physics ML / Foundation Models for the Physical World
About FiberMind
I’m building FiberMind to turn existing fibre‑optic networks into an intelligent sensing fabric for rail, borders and pipelines – physics‑aware foundation models on top of the world’s fibre, not another chatbot.
What you’d own
* Architecture and training of physics‑grounded models on noisy real‑world sensor data
* End‑to‑end ML: simulations + synthetic data → models → deployment with real operators
* Technical roadmap and early technical hiring
* Co‑designing pilots with rail / infra customers
Who this is for
* 5–10+ years in applied ML / scientific ML / signal processing (geophysics, CFD, inverse problems, etc.)
* You’ve shipped real systems, not just papers – ideally in sensing, robotics, or other physical‑world systems
* Comfortable working with messy, long‑horizon infra, not just web A/B tests
* Interested in co‑founding: you want real equity, real responsibility, and you’re okay that this will be hard and non‑linear
What I’m offering
* True co‑founder role with meaningful equity
* Direct access to rail / infra customers and pilots (not a science project)
* Room to design the entire technical stack your way, with support from a founder who’s spent ~15 years in fibre sensing and helped scale a previous company to ~£25m ARR
Founder’s note
I’ve spent 15 years in fibre sensing, from R&D labs to leading global commercial teams, and watched the tech over‑promise and under‑deliver. FiberMind is my answer: we’re building foundation models that turn existing fibre networks into a predictive nervous system for rail, borders and pipelines. Simple interface on the outside, learning engine underneath. If you care about physics, messy real‑world data and building a generational infra company, you’ll like this.