Senior AI Researcher, World Foundation Models

What you'll do

• Research, implement, and validate model architecture and algorithm changes to improve video generation fidelity.
• Prototype improvements for spatial multimodal modeling, modality alignment, and flow-based or diffusion-based video generation.
• Optimize training and inference efficiency using distillation, pruning, compression, and compute/memory optimizations.
• Define training objectives to improve sim-to-real generalization for human motion, contact, and interaction dynamics.
• Develop domain-specific benchmarks for evaluating world foundation models in physical and simulated environments.
• Translate research results into production-grade checkpoints, training code, and model integrations.
• Diagnose visual artifacts using perceptual metrics, human preference signals, and learned evaluators.

What we're looking for

• PhD in Computer Science, Graphics, Computer Engineering, or a closely related field or equivalent experience.
• 8+ years of applied research and/or industry experience in vision, graphics, or adjacent ML domains.
• 3+ years of direct experience designing, training, and evaluating generative models for image, video, or audio.
• Hands-on experience improving generative models with a focus on perceptual quality and temporal stability for generating humans.
• Advanced proficiency in Python, PyTorch, C++, and CUDA with strong research-engineering practices.
• Experience training and debugging large models in multi-GPU and/or multi-node environments and distributed training workflows.
• Practical knowledge of inference/runtime bottlenecks and optimization techniques.
• Proven track record in related research, including publications in top conferences like NeurIPS, CVPR, or ICLR (preferred).