Senior Backend & GPU Infrastructure Engineer – Headless ComfyUI / AI Video Pipeline
Budget: $15.0 - $25.0
HOURLY / PART_TIME
⭐ 4.94 (55)
Singapore
api-development, api-integration, automatic-deployment-pipeline, python, docker
Qualifications préférées
- Expérience : Intermédiaire
We are building an AI Video Generation SaaS Platform, and are looking for an experienced Backend & GPU Infrastructure Specialist to design and deploy our cloud video generation backend pipeline.
We plan to self-host high-performance open-source video models (such as LTX-Video, MiniMax Hailuo / Wan) on cloud GPU platforms (RunPod, Vast.ai, Modal), using ComfyUI in headless/API mode integrated into our core API backend.
Key Responsibilities
ComfyUI Pipeline Automation: Convert video generation workflows into headless ComfyUI API blueprints (prompt JSON execution) that run programmatically without UI overhead.
GPU Cloud Infrastructure & Deployment: Deploy, containerize (Docker/CUDA), and manage GPU instances on providers like RunPod (Serverless / Network Volumes), Vast.ai, or Modal.
Async Queue & Job Management: Build a scalable, fault-tolerant job queue (Redis + Celery / BullMQ / FastAPI) to queue incoming user video requests, track render progress, and deliver Webhook/WebSocket updates to our web frontend.
Storage & CDN Integration: Set up fast, direct uploads of finished video outputs to cloud storage (S3 / Cloudflare R2 / DigitalOcean Spaces) with signed CDN links.
Autoscaling & Cost Optimization: Implement cold-start optimization and auto-scaling logic to keep operational GPU costs low during low-traffic periods while handling spikes smoothly.
Required Experience & Tech Stack
AI Media Pipelines: Proven experience running headless ComfyUI API workflows for image/video generation at scale.
GPU Cloud Providers: Hands-on deployment experience with RunPod (Serverless or Pods), Vast.ai, Modal, or Salad.
Backend Languages: Strong proficiency in Python (FastAPI / Celery) or Node.js/TypeScript.
Infrastructure & Storage: Docker, CUDA drivers, PyTorch model deployment, Cloudflare R2 / AWS S3.
Asynchronous Architecture: Redis, Webhooks, or WebSockets for live job status reporting.
Preferred Qualifications
Prior experience building commercial AI SaaS media generation platforms (image, voice, or video).
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