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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