3D Machine Learning Engineer (f/m/d)

ppYou'll join our core 3D AI team: researchers and engineers working across the entire 3D stack: from raw data capture and geometric reconstruction to neural rendering and generative material synthesis. The team bridges academic rigor and production reality, moving fast without losing depth. Collaboration is close, hierarchy is flat, and the problems are genuinely hard. /p h3What This Role Could Look Like /h3 pThis is an open call for talented people working in 3D; whether your background is in computer vision, rendering, or machine learning. We're not hiring for a fixed spec; we're looking for people who are excellent in at least one of these areas and curious about the others. /p pDepending on your background and interests, you could be working on: /p pb3D Computer Vision Reconstruction /b /p pBuilding the geometric backbone of our scanning pipeline: multi-camera calibration, feature-based reconstruction, structure-from-motion, and high-precision mesh optimization. Integrating learned components where they outperform classical methods. /p pbInverse Rendering /b /p pDeveloping learning-based systems that recover geometry and physically-based materials from captured imagery—NeRF variants, Gaussian splatting, differentiable rendering, material decomposition, and relighting pipelines. /p pbNeural Rendering Material Systems /b /p pDesigning BRDF models and material representations, building diffusion-based rendering pipelines, and developing intrinsic decomposition models that separate albedo, shading, and material properties from real-world captures. /p h3Fields of Work /h3 ul liMulti-camera calibration, SfM, bundle adjustment, mesh processing /li liInverse rendering: material and geometry estimation from images /li liDifferentiable rendering and appearance decomposition /li liGenerative 3D reconstruction: diffusion-based approaches, feed-forward networks /li liBRDF modeling and physically-based material synthesis /li liIntegration of classical and learned components into production pipelines /li /ul h3Qualifications /h3 ul liMaster's or PhD in Computer Science, Computer Vision, Computer Graphics, Robotics, or a related field /li li3+ years of hands‑on experience in at least one of the areas described above /li liSolid understanding of either multi-view geometry, physically-based rendering, or generative models applied to 3D (diffusion, latent representations) /li liAbility to move between research and production, prototyping fast and shipping clean code /li liStrong programming skills in Python and/or C++ /li /ul h3Nice to Have /h3 ul liExperience with differentiable rendering frameworks (Mitsuba 3, nvdiffrast, PyTorch3D) /li liCUDA or GPU-accelerated geometry/rendering pipelines /li liFamiliarity with structured light systems, photogrammetry, or appearance capture /li liPublished research or open-source contributions in 3D vision, graphics, or ML /li liExperience with USD/MaterialX, Unreal, or real-time rendering pipelines /li /ul h3Benefits /h3 ul liCompetitive salary and stock options /li liVisa sponsorship and relocation support /li liFlexible working hours and remote work policy /li liParticipation in SIGGRAPH, CVPR, and global AI conferences /li liLunch vouchers, coffee bar and gym access (Durst AG campus) /li liA research environment with real production impact and world-class clients /li /ul /p #J-18808-Ljbffr