---
title: "Founding Machine Learning - World Models"
company: "One Robot"
company_url: "https://www.remjobs.works/companies/one-robot"
url: "https://www.remjobs.works/job/one-robot-founding-machine-learning-world-models-3eeacc32-6d89-4e48-b10d-0531ff2048fd"
apply_url: "https://jobs.ashbyhq.com/onerobot/084b67a9-db33-433b-bd81-e131a359b0a7"
workplace: onsite
location: "San Francisco"
employment_type: full-time
seniority: founding
role: ai-machine-learning
region: united-states
skills: ["python", "pytorch"]
date_posted: 2026-08-05T15:25:26.095Z
first_seen_by_remjobs: 2026-08-27T09:27:35.678Z
---

# Founding Machine Learning - World Models

**One Robot** — San Francisco

Apply: https://jobs.ashbyhq.com/onerobot/084b67a9-db33-433b-bd81-e131a359b0a7

## About One Robot

One Robot builds simulation environments that are realistic to see and realistic to interact with, so robotics teams can train and evaluate robot policies without being bottlenecked by robot time.

Today, improving a VLA often means more real-world hours: setting up the scene, running trials, resetting, and repeating. This loop is slow, expensive, and hard to scale. For example, material handling and manufacturing assembly tasks, models need far more training and evaluation data than teams can collect in the real world.

We use task-specific data to build world model-based simulation environments for hard manipulation tasks (for example, textiles and box folding). These environments help teams run more training and evals, find failure modes faster, and accelerate iteration on action policies with less dependence on real-world data collection and robot availability.

## About the role

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.

---

Source: One Robot's own career page, read by RemJobs. Canonical HTML version: https://www.remjobs.works/job/one-robot-founding-machine-learning-world-models-3eeacc32-6d89-4e48-b10d-0531ff2048fd