Applied AI Scientist, Multimodal Intelligence

What you'll do

• Conduct applied research experiments to bridge the gap between research advances and practical generative AI applications.
• Evaluate and adapt emerging research in multimodal foundation models for product integration.
• Develop robust solutions by transforming promising research ideas into production-ready features.
• Manage large-scale data pipelines including curation, preprocessing, and efficient storage.
• Fine-tune and optimize large foundation models for deployment on specific hardware.
• Build autonomous or semi-autonomous agents involving planning, task decomposition, and multi-step reasoning.
• Implement privacy-preserving or on-device machine learning techniques for consumer products.
• Define new research directions in multimodal pre-training, vision-language models, and video-language models.

What we're looking for

• Master's degree or equivalent practical experience in Computer Science, Machine Learning, Computer Vision, or a related technical field.
• PhD or equivalent practical experience in Computer Science, Machine Learning, or a related technical field.
• Experience in deep learning with demonstrated work in at least one area of multimodal systems such as vision, language, or video.
• Proficiency in Python and modern deep learning frameworks like PyTorch or JAX.
• Experience with rapid prototyping, reproduction, and validation of research ideas.
• Demonstrated expertise through a publication record in relevant conferences or a track record of applying deep learning to real-world products.
• Experience with foundation models, large-scale data pipelines, and fine-tuning or optimizing large models for production deployment.
• Familiarity with privacy-preserving or on-device machine learning and experience building autonomous agents using foundation models.