SpAItial is pioneering the development of a frontier 3D foundation model, pushing the boundaries of AI, computer vision, and spatial computing. Our mission is to redefine how industries, from robotics and AR/VR to gaming and movies, generate and interact with 3D content.
We’re seeking a 3D Graphics & Rendering Engineer to lead the creation and optimization of high-quality synthetic datasets that power our models. You’ll design scalable rendering pipelines, implement advanced rendering techniques, and work closely with research and engineering teams to ensure our data is accurate, diverse, and ready for training the next generation of spatial AI.

KEY QUALIFICATIONS

• Strong experience in computer graphics and rendering, with proven projects or shipped products.
• Deep understanding of 3D representations (meshes, voxels, point clouds, implicit surfaces, etc.).
• Proficiency in Blender, Unity, Unreal Engine, or similar rendering and simulation software.
• Experience with WebGL or other web-based 3D graphics frameworks.
• Bachelor’s, Master’s, or equivalent experience in Computer Science, Graphics, or related fields, OR 2+ years of industry experience in graphics and rendering.

PREFERRED QUALIFICATIONS

• Knowledge of NeRF, 3D Gaussian Splatting, or related volumetric rendering methods.
• Experience with procedural generation tools and techniques.
• Understanding of generative modeling techniques, including VAEs, GANs, and transformers.
• Background in large-scale data workflows for AI/ML model training.
• Track record of open-source contributions, published research, or community engagement in computer graphics or generative AI.
  At SpAItial, we are committed to creating a diverse and inclusive workplace. We welcome applications from people of all backgrounds, experiences, and perspectives. We are an equal opportunity employer and ensure all candidates are treated fairly throughout the recruitment process

• Design and optimize high-quality synthetic datasets for training large-scale 3D foundation models.
• Enhance and scale our synthetic data generation pipelines to improve efficiency, fidelity, and diversity of outputs.
• Integrate and refine rendering workflows using tools like Blender, Unity, or equivalent platforms.
• Work with with research team to ensure datasets align with model training objectives.
• Evaluate and maintain data quality, ensuring consistency and performance
• Stay ahead of industry trends in computer graphics, synthetic data generation