ALLSIDES is a Deep-Tech startup from the European Alpine region, that secured significant funding in early 2025 (announced under our former name Covision Media) and is experiencing rapid growth. We're redefining how the world experiences 3D content. By combining physically accurate scanning and generative AI, we enable new content creation workflows for e-commerce, virtual environments, and immersive experiences. Our clients include global brands like adidas, Meta, Amazon, and Zalando. Using our own scanners, we've built one of the world's largest datasets of photorealistic, relightable 3D assets with accurate ground truth—capturing at production scale (tens of thousands annually) while simultaneously training next-generation AI models. Meta uses our scanning technology for their HOT3D dataset (ECCV 2024). We collaborate with Prof. Cremers at TU München, Prof. Rother at Heidelberg University's Computer Vision Lab, and are advised by Prof. Pietro Perona from Caltech. As a research-driven startup and NVIDIA Inception member, we operate at the forefront of 3D machine learning and visual computing. More info about us and our technology: Website: Position Overview We are looking for a 3D Machine Learning Engineer with deep expertise in neural rendering, inverse rendering, and generative 3D methods. You will develop learning-based systems that recover high-fidelity geometry and physically-based materials from captured imagery—pushing the boundaries on relighting, material decomposition, and generative reconstruction. This role sits at the intersection of deep learning and graphics. If you want to ship neural 3D systems at production scale while advancing the state of the art, this is for you. Key Responsibilities Development of Neural 3D Systems Build and optimize neural inverse rendering models for geometry and material estimation. Develop relighting and appearance decomposition pipelines using differentiable rendering techniques. Explore generative r