Creative ML Technologist, Parallel Domain

• ComfyUI experience: You have demonstrable experience building multi-step ComfyUI graphs and compile and deploy open sourced projects through wrappers. This includes building projects from source, compiling them as needed, and integrating them to keep workflows readable, reusable
• Creative and technical skill: You combine strong creative sensibilities with practical, hands-on machine learning skills
• Python and ML proficiency: Solid Python and PyTorch fundamentals with hands-on experience, including tensor shapes, dtypes, autocast or no-grad, memory-aware batching, and devices
• Workflow design and evaluation: You have experience assembling perception and generative workflows for visual tasks and evaluating tradeoffs with simple, meaningful metrics
• VFX/Games production experience: Professional experience in VFX or game development with practical knowledge of content creation pipelines and cross-functional collaboration
• Clear communication: You have the ability to explain complex findings clearly and effectively to both creative and engineering stakeholders

Desirable

• We are looking for a Creative ML Technologist to prototype and evaluate model-driven workflows that our product and engineering teams can adopt quickly
• Using ComfyUI, you will combine generative models with perception models to drive generative editing and synthesis
• You will turn ambiguous creative goals into tested, repeatable processes with measurable outcomes, compare alternatives with clear evidence, and publish concise reports and reusable workflows
• Compose workflows: You will run focused experiments that answer product questions using ComfyUI graphs that combine perception and generative steps
• Measure and compare: You will produce side-by-side comparisons with qualitative frames and a set of meaningful metrics to guide decision-making
• Custom nodes and integrations: You will develop, implement, and deploy custom ComfyUI nodes for novel functionality and create wrappers for new open-source models
• Document and guide: You will document inputs, controls, expected artifacts, and typical failure modes in concise how-to notes and manifests so others can rerun and extend your work
• Collaborate and iterate: You will partner closely with creative users to refine and validate the visual output and work with engineering to hand off proven workflows for scaling