Design and advance state-of-the-art generative AI models across multimodal domains
Improve AI efficiency across the stack: kernel/graph optimization, model compilation, compression
Collaborate cross-functionally to bring innovations into production
Translate research breakthroughs into impactful product features
Contribute to AI community via top-tier conference publications

🎯 Requirements

Strong expertise in foundation models (diffusion models, LLMs, VLMs)
Experience in AI efficiency: kernel/graph optimization, quantization, distillation
Proficient in Python, PyTorch, Transformers, Diffusers, Megatron, DeepSpeed
Track record of publications (NeurIPS, ICML, ICLR, CVPR) or open-source contributions
Clear communication and cross-team collaboration skills

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