ComfyUI is a node-based workflow company that gives creators granular control over image, video, and audio outputs from diffusion models.
The Role We're looking for someone who loves optimizing model inference to join us in building the core of ComfyUI - the most complex and bleeding-edge part of our engine. You'll be working on making AI models run faster and more efficiently than anyone thought possible. You are a good fit if this describes you: - You geek out about model inference, torch optimizations, and memory management - You've written production PyTorch code that pushes performance boundaries - You love diving deep into how models actually work under the hood - You get excited about making insanely optimized code that just works - You think the current state of ML deployment could be way better What you'll do: - Build and optimize the core inference engine that powers ComfyUI - Make massive models run faster and use less memory than anyone else - Work directly with our core team on architecting new features - Tackle the hardest technical problems in the visual AI space - Help shape where we take this technology next Bonus: If you've worked with diffusion/LLM models before or built custom nodes for ComfyUI, that's awesome