AI and Computational Geometry Engineer
Atomicmachines · Emeryville, California
About this role
**Atomic Machines — AI and Computational Geometry Engineer** Atomic Machines is ushering in a new era of micromanufacturing with its **Matter Compiler™** technology platform. This platform enables new classes of micromachines by providing manufacturing processes and a materials library that are inaccessible to semiconductor manufacturing methods. The Matter Compiler™ is a **fully programmable, multi-process, multi-material** system—bits and raw materials go in, and complete, functional micromachines come out. --- ## About the Role The Matter Compiler will take a device design and produce a physical part **without manual translation steps**. In this role, you own the reasoning as software: the **DFM (Design for Manufacturing) function** inside the Atomic Machines CAM stack. You’ll build the full DFM layer, including: - The geometry between a device model, the workpiece, and machine processes - How parts are arranged on a blank and held in place during cutting - DFM rules for each process and material the platform supports - Constraints and checks that surface infeasibility at design time - Physical models that ground those rules in what the processes do to the part You’ll connect **design engineers’ geometry** with **process engineers’ intuition and results**, working cross-functionally across **AI, Modeling & Simulation, Design, and Process Engineering**. --- ## What You’ll Do - **DFM as a software capability:** Build algorithms, representations, and constraints that convert device geometry into process-executable geometry (including arrangement, retention, and release). - **Manufacturability constraints in the design loop:** Encode what the processes can and cannot do so infeasibility surfaces at design time. - **Bridge process intuition and code:** Work with design and process engineers to elicit judgment, formalize it, and make it auditable and testable. - **Physical grounding:** Move DFM decisions from heuristics toward criteria based on process mechanics (with Modeling & Simulation). - **Validation against reality:** Define correctness for layouts, test against fab runs, and feed failures back into constraints and models. - **The knowledge base:** Turn production history into a structured record for calibration, regression testing, and eventually learned components. --- ## What You’ll Need - **Experience level:** Not tied to a specific level; spans early career through Staff (L4–L6). Minimum **5 years** relevant industry experience, or a **PhD** in a related field. - **Practical DFM experience:** Evidence you wrote code that generates geometry under real manufacturing constraints (e.g., slicer/toolpath software for additive manufacturing, non-standard toolpathing, sheet metal stamping/tool & die design automation, PCB/lead frame layout, or comparable geometry-constrained automation). - **Computational geometry skills:** 2D boolean operations, polygon offsetting, packing and no-fit-polygon style reasoning. - **Strong software engineering:** **Python** plus a systems language; comfort driving geometry kernels/libraries via APIs (e.g., Shapely, Clipper, OpenCascade, CGAL, or similar). - **Track record on novel, poorly specified problems:** Open source contributions, patents, or industry work on greenfield problems count. - **Physical evidence mindset:** Willingness to ground work in fab evidence and iterate with process engineers. - **Education:** BS/MS/PhD in Mechanical Engineering, Computer Science, Applied Math, Computati
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