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About CoLab
At CoLab, we want to help mechanical engineering teams bring life-changing products to market years sooner.
CoLab is a cloud based platform for engineering design review. We make it easy for subject matter experts (SMEs) across your business to access, evaluate, and comment on 2D drawings and 3D models. Our built-in AI peer checker, AutoReview, scans designs for common errors or non-compliance with your standards and guidelines. AutoReview creates markups and comments on your files, in context – just like a human checker.
With CoLab, human SMEs and AI work together to help you make better decisions and improve designs faster. We automatically capture knowledge from across your global business that would otherwise be buried in emails, spreadsheets, slide decks, and unknown locations in Sharepoint or PLM. Then, we make sure every lesson learned and every design guideline is applied exactly when it matters.
Companies like Johnson Controls, Komatsu, Schaeffler, and Polaris have launched products 40% faster, cut BOM costs by 50%, and reduced quality escapes by 15% in 1 year.
About the RoleThis is a new, hands-on role designed to bridge a critical gap between mechanical engineering domain expertise and how our ML-powered evaluation tools operate. You’ll be the go-to Mechanical Engineer helping the team validate and improve AutoReview — our internal system that uses AI to classify and assess mechanical designs at scale.
You’ll run hundreds of design files through AutoReview, interpret the results, and help the team understand: Are we getting meaningful insights? What are we missing? What should change in how we prompt the system? Your analysis will directly shape how CoLab uses LLMs and machine learning to automate design feedback — one of our most ambitious and technically challenging projects to date.
If you’re energized by the idea of blending traditional mechanical engineering with next-gen AI tooling, and you thrive in early-stage product ambiguity, you’ll find this role deeply rewarding.
Our Ideal CandidateYou’re a mechanical engineer with strong instincts around design quality and lifecycle workflows — maybe you’ve worked in or alongside a design firm, or have spent time on the tools yourself. You’re curious and comfortable digging into data-heavy workflows, and you don’t mind reviewing a hundred outputs to get to a real insight.
You don’t need to be an AI expert — but you’re excited to learn how prompting, LLMs, and AutoReview work. You can sit down with a Dev or ML Engineer and clearly articulate, “This result isn’t useful because it’s missing X, Y, and Z.”
You’re opinionated enough to spot a flaw in a system, but humble enough to ask questions first. You’re still close to the work of mechanical design and aren’t afraid to dive into the weeds — but you’re also energized by new ways of doing things.
What You’ll Be Responsible ForRunning design evaluations through AutoReview, analyzing results, and classifying output qualityIdentifying gaps in model performance and communicating them clearly to ML and product teamsCollaborating with internal experts to triangulate insights and evolve internal systemsSupporting prompt tuning and testing to improve how we communicate with LLMsProviding ongoing feedback that helps us train AutoReview on the kinds of issues real engineers care aboutActing as a domain expert to help CoLab better understand the real-world context behind the data.
QualificationsMust-Haves
Nice-to-Haves
In your first 90 days, you’ll:
Get up to speed on AutoReview with support from our Solution Engineers and a tailored onboarding planEvaluate hundreds of outputs and provide feedback that drives measurable improvements in model performanceHelp uncover patterns in how engineers interpret results — and use those insights to tune our systemBecome a trusted internal expert for the product and applied ML teams when it comes to mechanical design judgment
Extra DetailsEquity Note
Frequently cited statistics show that people who identify with historically marginalized groups are likely to apply to jobs only if they meet 100% of the qualifications. We encourage you to help us break that statistic and apply even if you don’t meet every single qualification — your potential is what matters most to us.
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