Research Engineer - 3D World Models

The role

A Research Engineer will develop generative 3D machine learning methods to create physically-grounded 3D environments. The role involves building, training, and optimizing models for 3D reconstruction and world generation.

What you will do

• Design and develop generative 3D machine learning methods from images, video, and other inputs.
• Build, train, optimize, and evaluate models for 3D reconstruction, novel view synthesis, and world generation.
• Implement and experiment with 3D representations including point clouds, meshes, and 3D Gaussian Splatting.
• Develop training pipelines and loss functions to improve geometry accuracy, visual fidelity, and consistency.
• Collaborate with researchers to integrate physics-aware priors and world model capabilities.
• Analyze model performance, debug failure cases, and iterate to improve quality and robustness.

Required qualifications

• 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.
• Experience in model training and optimization.
• Ability to implement research papers, run experiments, and iterate quickly on new ideas.
• Strong coding skills.
• Passion for building reliable, scalable ML systems.

About the company

SpAItial is pioneering the next generation of World Models, pushing the boundaries of generative AI, computer vision, and the simulation of reality.