Member of Technical Staff - World Models

What you'll do

• Design, train, and scale models across visual and spatial modalities; develop multimodal learning and control methods.
• Improve sequence modeling, post-training, and model efficiency through research and experimentation.
• Build evaluations and collaborate with data, systems, and robotics engineers to turn research into reliable capabilities.

What they ask for

• PhD in Computer Science, Engineering, or a related technical field, or equivalent experience.
• Experience training machine learning foundation models end to end, strong PyTorch skills, and hands-on distributed training experience.
• Ability to independently design, execute, and analyze machine learning experiments.
• Experience developing evaluations that reveal model limitations and inform research decisions.

Nice to have

• Research contributions or publications on image, video, 3D, or multimodal models; experience with learned representations, compression, or tokenization.
• Experience with conditional generation, temporal consistency, long-context modeling, reinforcement learning, embodied AI, post-training, distillation, efficient inference, large-scale visual or sensor datasets, or open-source ML projects.

Tools

PyTorch

AI focus

Research and develop multimodal foundation world models for Physical AI, including generative and predictive modeling, multimodal learning and control, sequence modeling, post-training, optimization, and evaluation.