ASOS
E-Commerce
SeniorAppliedDiffusionEngineer
Neural analysis suggests this role is
optimal for mid candidates.
“Senior Applied Diffusion Engineer at ASOS. Skills: Diffusion models, LoRA pipelines, Image generation, Fashion AI. Design LoRA pipelines. Design fine-tuning pipelines”
What You'll Achieve.
Accelerate creative production; Accelerate styling workflows; Enhance customer experiences
Industry & Context.
Troubleshooting
What They're Looking For.
Must Have
Experience with PyTorch, Experience with diffusion models, Hands-on experience training LoRAs, Hands-on experience training DreamBooth models, Hands-on experience fine-tuning large vision models, Experience with Flux, Experience with Stable Diffusion XL, Experience with Diffusers, Experience with ComfyUI, Experience with ControlNet, Experience with IP-Adapter, Understanding of computer vision concepts, Experience building production ML systems, Experience building inference pipelines, Python engineering skills
Nice to Have
Experience with GPU optimisation, Experience with CUDA fundamentals, Experience with TensorRT, Experience with ONNX, Experience in fashion, Experience in e-commerce, Experience in creative tooling, Experience in gaming avatars, Experience in virtual try-on
What You'll Do.
Design LoRA pipelines
Design fine-tuning pipelines
Train fine-tuning pipelines
Optimise LoRA pipelines
Optimise fine-tuning pipelines
Develop controllable image generation systems
Build production-ready ComfyUI workflows
Build custom ComfyUI nodes
Create outfit generation pipelines
Create visual styling pipelines
Improve generation consistency
Improve garment fidelity
Improve brand alignment
Collaborate with Studios
Collaborate with Design
Collaborate with Marketing
Collaborate with Product teams
Operationalise GenAI workflows
Develop evaluation frameworks
Work closely with platform engineers
Optimise inference performance
Optimise GPU utilisation
Research multimodal AI
Prototype multimodal AI
Research fashion generation
Prototype fashion generation
How You'll Work.
Team & Collaboration
Studios; Design; Marketing; Product teams; Platform engineers
Full Job Description
We're ASOS, the online retailer for fashion lovers all around the world. We exist to give our customers the confidence to be whoever they want to be, and that goes for our people too. At ASOS, you're free to be your true self without judgement, and channel your creativity into a platform used by millions. Everyone needs some help showing up as their best self. We're Disability Confident Committed - let our Talent team know if you need any reasonable adjustments throughout the recruitment process The Senior Applied Diffusion Engineer will lead the development of controllable image generation systems focused on fashion, styling, and visual consistency. This role will design and productionise LoRA pipelines, outfit generation systems, virtual styling workflows, and advanced diffusion-based capabilities powering both internal creative tooling and future consumer-facing experiences. We are building an internal AI fashion generation platform to accelerate creative production, styling workflows, and next-generation customer experiences. The platform is centered around state-of-the-art diffusion models, controllable generation pipelines, and proprietary fashion data. Key Responsibilities * Design, train, and optimise LoRA and fine-tuning pipelines for fashion-specific generation tasks. * Develop controllable image generation systems using Flux, SDXL, ControlNet, IP-Adapter, and related tooling. * Build production-ready ComfyUI workflows and custom nodes. * Create outfit generation and visual styling pipelines grounded in ASOS product and styling data. * Improve generation consistency, realism, garment fidelity, and brand alignment. * Collaborate with Studios, Design, Marketing, and Product teams to operationalise GenAI workflows. * Develop evaluation frameworks for image quality, style accuracy, and model performance. * Work closely with platform engineers to optimise inference performance and GPU utilisation. * Research and prototype new approaches in multimodal AI, and fa
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