Research Scientist, Foundation Model

📋 Description

• Lead research and development on pre-training and mid-training of multimodal foundation models at
• Design novel algorithms for high-fidelity, real-time multimodal synthesis across text, image
• Develop scalable data pipelines and model training strategies for diverse datasets.
• Advance diffusion, autoregressive, and other generative techniques for large-scale pre-training and
• Collaborate with engineering/product teams to bring research into production systems.
• Publish in top conferences/journals and communicate work internally and externally.

🎯 Requirements

• 5+ years of research in large-scale pre-training/mid-training of multimodal foundation models
• Strong publication record (e.g., NeurIPS, ICML, ICLR).
• Hands-on experience with large-scale multimodal model design, training, and deployment.
• Deep understanding of generative architectures (diffusion, autoregressive, cross-modal).
• Expertise in high-throughput dataset curation and model pipeline optimization.
• Proficiency in Python, PyTorch, TensorFlow; production deployment experience.

🎁 Benefits

• Competitive salary and substantial equity in a high-growth startup
• Full health benefits + 401k matching and more
• Collaborative, mission-driven team with major growth opportunities
• Flexible on-site/remote hybrid (HQ in Palo Alto, CA)