CAD and AI-powered engineering for automotive manufacturing and product design
广州科锐特 operates at the intersection of mechanical CAD design and AI-based simulation, with a tech stack spanning CATIA, AutoCAD, SolidWorks, and deep-learning frameworks (TensorFlow, Caffe, YOLO). The hiring profile—engineering-heavy, mid-to-senior weighted, zero sales roles—and active projects (transmission feasibility analysis, production-line optimization, mass-production support) suggest a B2B vendor focused on automotive OEM engineering rather than consumer-facing software. Current pain points cluster around manufacturing efficiency and production-line modernization.
广州科锐特生物科技有限公司, based in Guangzhou, builds engineering and manufacturing optimization solutions for automotive and industrial sectors. The company combines mechanical CAD tooling (CATIA, AutoCAD, SolidWorks, UG NX) with AI-driven simulation and analysis (TensorFlow, YOLO for computer vision, MotorCAD for thermal/electric motor design). Active project portfolio spans new vehicle drivetrain design (MCP/MCS), hybrid transmission feasibility studies, production-line equipment selection, and manufacturing process optimization. The organization operates with embedded engineering and manufacturing teams, supporting both new product development and production ramp cycles.
CATIA, AutoCAD, SolidWorks, UG NX, and CAXA. MotorCAD is used for motor and drivetrain simulation.
TensorFlow, Caffe, MXNet, and YOLO for computer vision. These tools support simulation analysis and production-line visualization tasks.
New vehicle drivetrain design, hybrid transmission feasibility analysis, production-line optimization, equipment selection simulation, and mass-production support for new products.