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Wood defect product owner

Neural Grader
Product Owner
Inserat online seit: 21 Mai
Aufgaben der Stelle

<p>We’re hiring: <strong>Wood Defect Product Owner </strong>at Neural Grader </p><p><br></p><p>Neural Grader is building AI for automated wood defect detection and grading in real industrial sawmill environments. </p><p><br></p><p> We are looking for an interdisciplinary profile: someone with a strong <strong>forestry / wood processing / lumber grading background</strong>, and digital competences who can own the quality loop of our AI defect models. </p><p> </p><p>Ideally, the person should have graduated from TH Rosenheim, Universität Hamburg (Wood Science), TU Dresden, or a similar wood engineering / wood science / forestry school. </p><p><br></p><p>This is not a classic support role and not a general coordination role. </p><p><br></p><p>The core mission is to own and improve the full <strong>data → model → customer feedback</strong> loop for defect detection: </p><ul><li>investigate real customer failure cases </li><li>understand whether the issue comes from data, annotation, model limitations, or production conditions </li><li>improve evaluation datasets and validation logic </li><li>work closely with annotation and ML teams </li><li>help turn raw customer feedback into clear, actionable priorities </li><li>shorten the loop from “model got it wrong” to “fix validated in production” </li></ul><p><br></p><p>You should be comfortable discussing wood defects with customers, reviewing real production cases, and working with technical teams to improve model quality over time. </p><p><br></p><p><strong>Ideal background:</strong> </p><ul><li>Forestry, Wood Engineering, Wood Science, or Wood Processing </li><li>strong practical understanding of wood defects and sawmill reality </li><li>attention to detail and structured thinking </li><li>ability to work with data, examples, quality issues, and technical workflows </li><li>good communication skills in customer and internal discussions </li></ul><p><br></p><p>This role sits at the intersection of <strong>wood expertise, AI model quality, annotation quality, and customer reality</strong>. </p><p> </p><p><strong>Ready to Apply? </strong>Were excited to hear from you! Send us your application and lets start the conversation about your future with us.</p>

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