Founding Machine Learning Engineer
One Robot
Founding Machine Learning Engineer
One Robot
World-model simulation environments for robotics teams
We build world models that simulate manipulation scenes faithfully enough to validate, and one day, train policies without touching a robot. You'll develop generative models that make this work, with the controllability and physical fidelity to match real-robot behavior.
What you'll do:
Train video and dynamics models: Develop world models with action conditioning for manipulation policies.
Push long-horizon coherence: Develop architectures and training methods that extend rollout quality on hard physical tasks.
Own training infrastructure: Run multi-GPU clusters, write custom CUDA, debug at scale.
Build the world-model data engine: Design, implement, and improve a data engine that allows the world model to compound learning across customers and manipulation tasks.
Requirements:
Very strong coding in Python and PyTorch (or similar).
Video generation experience: Deep experience training image or video generation models end-to-end.
Large-scale training: Track record operating training runs at cluster scale.
3D vision: Working knowledge of multi-view geometry, scene reconstruction, and physical priors.
One Robot provides world model-based simulation environments for robotics teams to train and evaluate Vision-Language-Actions (VLAs) for manipulation tasks. It builds task-specific world models by learning contact dynamics and visual appearance from a client’s robot data, creating photorealistic and physics-realistic simulations that handle challenging tasks like deformable objects and complex assemblies. These simulations let teams test and train policies faster, identify failure modes, and generate targeted synthetic data without relying heavily on real-world robot time. Unlike generic physics engines, One Robot’s models predict how objects move and deform in response to actions, enabling focused edge-case testing for manufacturing automation and material handling. The company aims to accelerate iteration on action policies, reduce data collection needs, and bring robust policies to production.
Explore more opportunities at One Robot