The next breakthrough in generative AI is to digitally synthesize dynamic 3D worlds. 3D world models enable us to create new content for games, adaptive digital twins of environments and synthetic worlds for training robots. But today’s 3D simulators and workflows are too hard to build and scale. Common Sense Machine’s mission is to build an AI that learns to autonomously translate multimodal inputs (images, text) into game-ready 3D worlds.

CSM is looking for an experienced research scientist with a track record of developing neural radiance fields and related architectures. You will be responsible for continually keeping in touch state of the art papers and integrating them into our production pipeline in collaboration with research and development teams.

Responsibilities:

• Conduct research and scale models at the intersection of NeRFs and diffusion models

• Collaborate with cross-functional teams to achieve project goals

Requirements:

• Implement, train, and improve state-of-the-art techniques to generate high-quality 3D assets

• Strong grasp of 3D graphics, computer vision, and deep learning

• Experience with differentiable rendering systems

• Proficiency in Python and PyTorch. CUDA is a plus, but not required.

• Excellent communication and collaboration abilities

• PhD in computer science or related field