Software Engineer (AI) (m/f) – 80-100%

ppSuccessful with AutoForm! AutoForm offers software solutions for sheet metal forming and BiW assembly process. With over 500 employees dedicated to this field, AutoForm is recognized as the leading provider of software for product manufacturability, tool and material cost calculation, die face design and virtual stamping as well as BiW assembly process optimization. All of the Top 20 automotive OEMs and most of their suppliers have selected AutoForm as their software of choice. Besides its headquarters in Switzerland, AutoForm has offices in Germany, The Netherlands, France, Spain, Italy, Czech Republic, Sweden, USA, Mexico, Brazil, India, China, Japan and Korea. AutoForm's AI revolution in numerical simulation AutoForm is pioneering the transformation of engineering simulations using advanced AI technology. Our innovative approach not only enhances the efficiency and accuracy of simulation technology, but also simplifies and accelerates the day-to-day tasks of our users with real, fully functional applications. By joining our team, you will have the opportunity to work on ground-breaking innovations in a dynamic setting. As AutoForm expands its AI capabilities, we are strengthening our R\D Department in Zurich with specialists who can combine machine learning, 3D geometry, simulation data and engineering insight. /ph3Software Engineer (AI) (m/f) -- 80-100% /h3h3Geometric Machine Learning /h3pPossible tasks Explore the forefront of innovation by working on AI solutions at the intersection of cutting-edge technologies such as FEM simulation, computer vision and geometry modeling. Contribute to the development and extension of AI-based technologies that combine synthetic data generation, numerical simulation and machine learning. Design and implement methods for processing, representing and analyzing complex 3D geometric data on mesh level. Apply simulation-driven data and surrogate-modeling techniques to efficiently learn from large-scale synthetic datasets. Contribute to the development of scalable AI pipelines integrating geometry generation, simulation, data preparation, model training and validation. Collaborate closely with experts in sheet metal forming, simulation technology, software engineering and machine learning. Work in an agile SCRUM team /ph3Your profile /h3ulliMachine learning and deep learning, including modern frameworks such as PyTorch or TensorFlow. /liliGeometric machine learning, U-Net, graph neural networks, mesh-based learning or related methods for 3D geometric data. /liliDevelopment of generative, predictive or surrogate models for engineering applications. /liliStrong understanding of mathematics, optimization and statistical learning methods. /liliExperience with synthetic data generation, simulation-based learning or data-driven engineering workflows. /liliUnderstanding of numerical simulation, manufacturing processes, CAE applications or related engineering domains. /liliGood software engineering skills and experience with object-oriented design and development. /liliProgramming experience in C++ and Python. /liliStrong analytical skills and ability to solve complex technical problems. /liliInterest in working at the intersection of AI, geometry and engineering simulation. /liliTeam player with strong communication and collaboration skills. /liliGood command of English. German is a plus. /li /ulh3Our offer /h3ulliA challenging role in a respectful and global working environment /liliBeing part of a world-leading, high-end CAE software company /liliWorking on cutting edge technologies for the automotive industry /liliProfessional development and continuous education /liliExcellent balance between your working life and your private life through flexible home office and flexible working hours /liliStart of work is 1st September 2026. /li /ulpPlease note that we only consider applicants that have the legal right to work in Switzerland. /ppAutoForm Development GmbH, Technoparkstrasse 1, 8005 Zürich, Switzerland Tel: + -- Careers Processing of applicant's personal data is based on our Data Privacy Policy . /p /p #J-18808-Ljbffr