AI Engineer
1 day ago
What Youll Own:
- Design production-ready GenAI pipelines:
Build and maintain node-graph and script-based workflows using ComfyUI, Stable Diffusion, and modern image/video models for key use cases such as keyframes, style transfer, image-to-video, text-to-video, upscaling, and repair. - Ensure visual consistency across shots
Design first-frame-controlled and reference-guided workflows that preserve characters, composition, lighting, and style across multiple frames and sequences. - Bridge creativity and engineering
Collaborate closely with GenAI artists, producers, and creative leads to translate creative intent into stable, reusable workflow templates. - Optimize for speed, cost, and quality
Profile and optimize pipelines through smart node selection, batching strategies, caching, and model loading optimizations—ensuring maximum GPU efficiency and minimal inference cost. - Expose workflows as services
Work with the Technical Director to package pipelines as APIs and internal services, with clear contracts, versioning, and documentation for easy integration by other teams. - Experiment and evolve
Continuously evaluate new models, nodes, and techniques (LoRA, ControlNet, IP-Adapter, video diffusion tools) to improve reliability, quality, and creative flexibility.
What You Bring:
- 1-2+ years of experience in technical media, VFX pipelines, creative coding, ML, or computer vision engineering.
- Strong hands-on experience with ComfyUI or similar node-graph systems, including deep familiarity with Stable Diffusion ecosystems.
- Solid understanding of LoRA, ControlNet, IP-Adapter, reference conditioning, and modern image/video generation models.
- Strong Python skills and experience using ffmpeg for programmatic image and video processing.
- Working knowledge of GPU resource management, inference optimization, VRAM constraints, and common generative model failure modes.
- Ability to think in systems—turning one-off experiments into repeatable, production-grade workflows.
- A portfolio of workflows, tools, demos, or repositories (GitHub or similar) is highly desirable.
Why Obbserv AI:
We're not retrofitting AI into old workflows; we're building the workflow layer of the future. At Obbserv AI, engineers and artists work side by side to define how generative systems are actually used in real campaigns, at real scale, for real brands.
Here, you won't just run models.
You'll architect the pipelines that turn imagination into repeatable reality.
If you're excited about building the invisible engines behind the most visible creative work this is where you belong.
Welcome to Obbserv AI.
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