Slate Studios

Design and implement a virtual try-on pipeline for ghost mannequin to on-model try-on. Ensure outputs meet luxury e-commerce quality and document the pipeline for internal use. | Proven experience with Stable Diffusion and related frameworks is essential. Strong knowledge of ControlNet and virtual try-on models is required, along with a portfolio of photorealistic outputs. | AI Virtual Try-On (VTON) / Stable Diffusion Engineer Freelance / Contract | Remote | Fashion & E-Commerce AI About Us We’re a content production company working at the intersection of fashion, technology, and creative media. Our clients expect photorealistic, high-quality imagery suitable for luxury e-commerce catalogs. We’re now building an AI-driven virtual try-on workflow that converts ghost mannequin product shots into model images with consistent faces, poses, and catalog-ready quality. Role Overview We’re looking for a Stable Diffusion / ComfyUI engineer with experience in ControlNet, IP-Adapter/InstantID, and virtual try-on (VTON) pipelines to help us set up a repeatable system. Responsibilities Design and implement a ComfyUI (or AUTOMATIC1111) pipeline for ghost mannequin → on-model try-on. Integrate ControlNet (pose/depth) for consistent body/angles (front/side/back). Apply IP-Adapter or InstantID for model face/hair consistency across all garments. Configure garment conditioning / VTON modules (e.g., IDM-VTON, GP-VTON) for accurate drape and print fidelity. Ensure outputs meet luxury e-commerce quality: neutral backgrounds, sharp garment edges, accurate fabric textures. Document the pipeline for internal use and train our team on running batches. Optional: Assist with post-processing automation (upscaling, seam cleanup, relighting). Requirements Proven experience with Stable Diffusion, ComfyUI, or similar frameworks. Strong knowledge of ControlNet (pose/depth) and IP-Adapter / InstantID. Hands-on with virtual try-on / fashion-focused diffusion models. Portfolio or examples of photorealistic AI model/garment outputs. Ability to deliver repeatable, production-ready pipelines (not just one-off generations). Strong communication and documentation skills. Nice to Have Experience with LoRA / custom training for garment fit or fabric fidelity. Familiarity with Python automation for batch jobs. Past work with fashion e-commerce imagery. What We Offer Freelance/contract engagement with potential for ongoing collaboration. Competitive project-based compensation ($3K–10K depending on scope and experience). Opportunity to shape an AI-first fashion production pipeline at scale. Flexible, remote-first collaboration with a fast-moving creative team. How to Apply Please submit: Your portfolio or sample outputs (ideally fashion/virtual try-on related). A short note describing your experience with ControlNet + IP-Adapter and any VTON models you’ve worked with. Your availability and estimated project rate.