spaitial - Research Engineer - 3D World Models
Requirements
• Bachelor's or Master's degree, or equivalent project/research experience, in computer science, machine learning, computer vision, graphics, robotics, or a related field. • Strong fundamentals in deep learning and generative models, in particular diffusion models and transformers. • Solid understanding of 3D processing concepts such as camera geometry, depth, reconstruction, point clouds, meshes, or Gaussian splats. • Proficiency in Python and deep learning frameworks such as PyTorch, with experience in model training and optimization. • Ability to implement research papers, run experiments, and iterate quickly on new ideas. • Strong coding skills and passion for building reliable, scalable ML systems.
Responsibilities
• Design and develop cutting-edge generative 3D machine learning methods for creating high-quality 3D content from images, video, and other inputs. • Build, train, optimize, evaluate models for 3D reconstruction, novel view synthesis, and world generation. • Implement and experiment with state-of-the-art 3D representations including point clouds, meshes, and 3D Gaussian Splatting. • Develop training pipelines and loss functions that improve geometry accuracy, visual fidelity, and consistency. • Collaborate with researchers to integrate physics-aware priors and world model capabilities into generative systems. • Analyze model performance, debug failure cases, and iterate rapidly to improve quality and robustness.
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