Senior Asset Pipeline Engineer, Sim-Ready Content

Genesis·RemoteRemotesenior

In short

→Construyes y mantienes una pipeline automática de activos 3D listos para simulación, desde entrada hasta salida valida.
→Diseñas nodos inteligentes con agentes (IA) que toman decisiones autónomas en el flujo, con verificación y fallbacks integrados.
→El enfoque clave es escalabilidad, reproducibilidad y calidad sin intervención humana, con énfasis en física y renderizado fotorealista.

Proficiency in English is required for collaboration with global teams.

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What they ask for

✓5+ años construyendo pipelines de activos 3D en juegos, VFX o simulación con propiedad de pipelines en producción.
✓Conocimiento profundo de formatos 3D: USD, glTF, FBX, OBJ, y formatos físicos como URDF/MJCF.
✓Expertos en Python y C++ para procesamiento rápido y eficiente.
✓Experiencia hands-on en procesamiento de mallas: reparación, decimación, UVs, composición convexa.
✓Dominio de materiales PBR, baking de texturas y gestión de espacios de color.
✓Capacidad para guiar herramientas DCC (Blender, Houdini, Maya) en modo headless y construir sistemas de trabajo por lotes o distribuidos.

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About Genesis AI Genesis AI builds the simulation platform powering the next generation of robotics and embodied AI. Our flagship product, Genesis World, is a unified multi-physics simulation engine paired with Nyx, our in-house GPU-accelerated, path-traced photorealistic renderer. Together they provide a platform for training robotics and embodied AI at scale; letting teams simulate complex physical worlds with high fidelity and speed, from a laptop to datacenter-grade GPUs, and close the gap between simulation and the real world. About the Role A simulator is only as useful as the content that runs inside it. Training embodied agents at scale means large volumes of assets that are simultaneously physically valid and visually convincing and that is a pipeline problem before it is an art problem. We're hiring a Senior Engineer to build the path from raw input to sim-ready asset: geometry from a range of sources going in; clean meshes, correct collision proxies, plausible physical properties, materials that hold up under a path tracer, and reliable metadata coming out. The bar is throughput and repeatability. An asset that needs a human pass to be usable doesn't scale, so the pipeline has to make good decisions on its own and flag the cases where it can't. Part of that autonomy comes from agents embedded in the graph itself. Nodes can call models to produce input content, drive generation, pick parameters, interpret a mesh before deciding how to treat it, or judge whether a result is acceptable. Making that reliable is its own engineering problem: agents are non-deterministic, they fail in ways a mesh operator doesn't, and they need guardrails, structured outputs, retries and verification around them. You'll be building that as a first-class part of the pipeline rather than bolting it on. You'll work closely with the stakeholders, who set direction and priorities. You own the technical design and the implementation and you're expected to bring enough pipeline experience to challenge the plan where it needs challenging.

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