My co-founder Ian and I combine over 15 years of industry experience, working with companies like SEW-Eurodrive, Terex, Bosch and Carl Zeiss. We co-founded Resourcly, a Project A-backed, industrial tech start-up to help industrial manufacturers streamline complex portfolios to improve EBIT while preventing and reducing idle inventory from being scrapped.
With our solution, we want to solve industry problems that we have tried to address for the last decade in the manufacturing companies we worked for, but that have so far been out of reach. With new technology and AI, that can finally happen.
Complex processes and products, lack of engineering talent and massive labour costs as well as a lack of intelligent automation have remained the industry's most pressing challenge. With LLMs and agents, we finally have the tools to solve this.
Our vision is that future purchasing and engineering processes will be orchestrated and run by an AI workforce - ensuring reliable and cost-efficient procurement and flow of goods in an uncertain and complicated world with finite resources.
🦾 We're already live with global manufacturing leaders in Europe
💰 Backed by one of Europe's top early-stage funds (Project A)
📈Growing fast and hiring exceptional talent to join early
Our goal is to build a small, but excellent team, therefore we are looking for a Senior AI/ML Engineer. If you are excited to work in a very early-stage environment alongside the founding team, stellar data scientists and engineers, using AI at the product core to solve meaningful problems - please reach out.
As our Senior AI/ML Engineer, you will own the AI brain of Resourcly—building intelligent data understanding, normalization, and semantic matching systems that turn heterogeneous industrial data into structured, comparable knowledge. This is a first-time hire for this role, meaning you'll have significant influence in shaping our AI/ML strategy and architecture from the ground up.
You will transform messy, real-world data—PDFs, images, JSON, XML, CSV, legacy formats—into structured, normalized representations that can be compared, matched, and reasoned about. You'll work closely with our Founding Engineer Soheil, developers, domain experts, and customers to build systems that extract meaning, normalize values, build relationships between entities, and enable intelligent functionality on top of this unified knowledge layer.