Former Carpenter Built an ML Startup by Solving Construction's Data Problem

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A carpenter-turned-founder with a finance background shares how he arrived at machine learning not through formal study, but by trying to solve a real problem in the construction industry. He founded ML Systems LLC in December 2025 and spent nine months building an app now live on both major app stores. His core challenge was creating a system to track and account for salvaged materials during home deconstruction, turning them back into usable resources for rebuilding. The project forced him to confront what he describes as an ontology problem — multiple professionals describing the same building in incompatible ways — rather than a simple data-cleaning task. Writing in response to a widely read machine learning career guide, he argues that domain-specific, self-sourced data and real-world problem ownership can replicate the portfolio signal that hiring managers actually look for.

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ProgrammingDEV Community ·

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