We are looking for a Principal Computational Engineer to join our partner's team!
Our partner operates in the technology-driven, on-demand manufacturing ecosystem, connecting global customers with manufacturing capabilities through an advanced digital platform. The company combines computational geometry, AI, and manufacturing intelligence to automate the journey from CAD design to manufacturable, priced, and production-ready parts.
In this highly senior individual contributor role, you will define the long-term technical direction of the company’s 3D geometry and Design for Manufacturability (DFM) platform. You will architect and build systems that transform complex customer CAD models into manufacturable parts across processes including CNC machining, sheet metal, additive manufacturing, injection molding, casting, and finishing.
Key Responsibilities
- Define and drive the multi-year technical roadmap for the company’s computational geometry and geometric reasoning platform
- Architect systems covering B-Rep ingestion and healing, feature recognition, DFM analysis, manufacturing process routing, geometric pricing signals, and CAM/CAE integration
- Design and implement core geometric operations including intersections, offsets, Boolean operations, projections, trimming, and NURBS curve and surface processing
- Establish technical standards for numerical precision, tolerancing, robustness, floating-point error management, and performance
- Develop resilient geometry-processing systems capable of handling complex and imperfect real-world CAD data
- Work with multiple CAD formats including STEP, IGES, Parasolid XT, JT, SLDPRT, CATPart, and DXF
- Combine classical computational geometry methods with modern AI/ML techniques to identify manufacturability risks and optimize manufacturing decisions
- Develop production-grade software primarily using C++ and Python
- Architect integrations between geometric intelligence, CAD environments, and industrial software ecosystems
- Translate research in computational geometry, geometric modeling, and computational fabrication into scalable production systems
- Collaborate with Product, Manufacturing Engineering, Pricing, ML, and Operations teams to translate business challenges into geometric and algorithmic solutions
- Lead technical design reviews and establish engineering standards across geometry-related systems
- Mentor Senior and Staff-level engineers and contribute to technical hiring and engineering calibration
- Contribute to publications, patents, open-source initiatives, and external technical collaborations where relevant
Qualifications
- M.S. or Ph.D. in Applied Mathematics, Computer Science, Mechanical Engineering, Computational Physics, or a closely related technical field
- Typically 12+ years of relevant professional experience, or a Ph.D. with 8+ years of relevant industry experience
- Deep expertise in computational geometry, geometric modeling, CAD/CAE, or simulation systems
- Strong knowledge of B-Rep topology, NURBS, parametric and free-form surfaces, trimmed surfaces, geometry healing, robust predicates, and spatial data structures
- Hands-on experience with geometric modeling kernels such as Parasolid, ACIS, CGM, Granite, ShapeManager, Open CASCADE, or pythonOCC
- Strong understanding of CAD interoperability and formats including STEP, IGES, JT, Parasolid XT, CATIA, NX, Creo, SolidWorks, and DXF
- Expert-level C++ (C++14/17/20) development experience and strong proficiency in Python
- Experience with tools and technologies such as CMake, GDB, sanitizers, profiling tools, SWIG, pybind11, NumPy, and Numba
- Strong mathematical foundation in linear algebra, numerical methods, multivariable and differential calculus, differential equations, floating-point analysis, and differential geometry
- Experience taking complex algorithms or research concepts from experimentation through to production
- Familiarity with AI/ML approaches for geometry, including graph neural networks, point-cloud and voxel representations, neural implicit representations, and geometry-aware learning methods
- Experience with cloud platforms such as AWS for large-scale computational workloads
- Understanding of manufacturing processes including subtractive, additive, formative, and finishing technologies
- Familiarity with manufacturing standards such as GD&T, ISO, and ASME Y14.5
- Demonstrated ability to provide technical direction, mentor senior engineers, and influence cross-functional technical decisions