Contact person: François

Phone:Show

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Location: Remote Cooperation

Budget: Recommended by industry experts

Time to start: As soon as possible

Project description:
"We're looking for an experienced ML/MLOps engineer to design and deploy an inference pipeline that generates high-quality AI images from text prompts. The goal is a reliable, production-ready system we can call via API to produce images at consistent quality, with reasonable latency and cost.Scope of Work- Select and deploy a state-of-the-art text-to-image model (e.g., FLUX, Stable Diffusion 3.5 / SDXL, or your recommendation based on our needs)- Build a clean inference API (REST endpoint) that accepts a prompt and parameters and returns generated images- Optimize output quality: schedulers/samplers, refiners, and upscaling where appropriate- Set up GPU-backed deployment- Optimize for latency, throughput, and cost; implement queueing/batching if needed- Provide documentation covering setup, API usage, parameters, and how to update or swap modelsRequired Skills- Strong experience with diffusion models and image-generation inference- Python + PyTorch; familiarity with Hugging Face Diffusers- GPU deployment and serving experience (containers, autoscaling, cold-start handling)- API development and basic security (auth, rate limiting)Nice to Have- Experience with LoRA, ControlNet, IP-Adapter, or fine-tuning- Prompt engineering and quality benchmarking- Cost-optimization on serverless GPU platformsDeliverables- Deployed, documented inference endpoint- Source code in a repository we own- Brief handoff doc or call" (client-provided description)

Additional information:"Remote" (admin-provided information)