Generative AI Artist Fashion - Freelance

INDG is expanding the way high-volume visual content is produced: from CGI and 3D pipelines into AI-assisted image generation, editing, and content orchestration. This role exists to help turn generative AI from an experimental layer into a reliable production capability.

As a Generative-AI Artist (freelance), you will build and run image generation workflows that support real client production: fashion, sportswear, product imagery, talent visuals, campaign adaptations, and asset variation at scale. You will work inside the tension that defines this role: fast-moving AI models, production deadlines, visual realism, brand consistency, and systems that other people can actually use.

INDG has spent 20+ years building visual production systems for global brands. Grip extends that heritage into AI-orchestrated content production. Your work will help teams generate, edit, refine, and scale imagery while keeping outputs sharp enough for enterprise brand use.

What You Will Do

Build and Maintain Generative Image Workflows

Set up, configure, and troubleshoot custom ComfyUI workflows for image generation, image editing, inpainting, outpainting, upscaling, relighting, variation generation, and controlled composition.

You will connect models, nodes, prompts, masks, ControlNet inputs, LoRAs, reference images, and post-processing steps into repeatable workflows. The goal is not a one-off good image. The goal is a workflow that can produce consistent, usable outputs across many assets.

Apply AI to Production Content Problems

Use generative AI techniques against real production needs: adjusting apparel/footwear/accessories/equipment imagery, refining fashion/sportswear product shots, extending scenes, improving model consistency, generating controlled variations, or supporting creative teams with rapid image exploration.

You should understand that production images are judged on details: skin texture, garment fit, fabric behavior, seams, logos, lighting direction, pose plausibility, background continuity, and whether the image still feels brand-correct after generation.

Adapt Quickly as Models and Tools Change

Work confidently across diffusion-based models, LoRAs, ControlNet, IP-Adapter-style workflows, segmentation tools, inpainting models, outpainting methods, face and identity consistency techniques, and emerging image-generation systems.

You will test new models, identify where they improve or break the pipeline, and help the team decide when a tool is production-ready. You do not need every new release to be perfect. You need to know how to evaluate it, isolate failure modes, and translate it into a usable workflow.

Support a Pipeline Used by Artists and Production Teams

Document workflows clearly enough for artists, producers, and technical teams to reuse them. Package settings, prompts, node graphs, model dependencies, and output criteria in a way that reduces guesswork.

You will work with CGI artists, creative technologists, production leads, and platform teams to connect creative intent with operational execution. When something fails, you trace the system: model choice, conditioning input, prompt structure, mask quality, render reference, node configuration, or post-process step.