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We're looking for an experienced ML researcher to push the boundaries of object-aware image editing models. You'll work on: Designing and training diffusion-based architectures for object removal and insertion; Leveraging EditNet (our high quality before/after dataset) to improve realism, fidelity, and control; Experimenting with new training strategies (loss functions, control signals, conditioning) to improve precision and scalability; Collaborating with engineers to bring research into production models powering millions of edits. Requirements: PhD or equivalent research experience in ML, computer vision, or generative models; Strong track record with diffusion models, transformers, or related architectures; Solid understanding of image editing tasks (inpainting, harmonization, relighting, compositing, etc.); Ability to go from research to production-quality code; Interest in building practical systems with real-world adoption. Nice to have: Experience with large-scale distributed training pipelines; Experience with video generation models; Contributions to open source ML libraries; Prior work on object-aware editing, inpainting, or compositional models. Apply at bonjour@lagon.tech