AI Engineer (World Models) at Foundation Robotics Labs Inc

San Francisco, California, United States -

Full Time

Start Date

Immediate

Expiry Date

10 Jun, 26

Salary

0.0

Posted On

12 Mar, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

World Models, Model-Based RL, Predictive World Simulators, PyTorch, JAX, Deep Learning Architectures, Transformers, Diffusion Models, Neural Radiance Fields, Variational Recurrent State-Space Models, Python, C++, Robotics Middleware, ROS2, Isaac Sim, MuJoCo

Industry

Robotics Engineering

Description

Why are We Hiring for this Role: We are building a general-purpose humanoid that must understand and navigate the physical world — and that requires a dedicated engineer to architect the internal models that make that possible World models are the cognitive backbone of our robot; without them, the humanoid cannot plan, predict, or adapt to novel environments We are at an inflection point where our hardware is ready — now we need the intelligence layer to match it The gap between a robot that executes fixed commands and one that truly reasons about its environment is a world model; we are hiring to close that gap As we scale to real-world deployment, our humanoid needs to generalize across unstructured, unpredictable settings — something only a robust world model can enable This hire will directly shape the core intelligence architecture of our platform before it becomes locked in at scale What Kind of person are we looking for Hands-on experience building world models, model-based RL, or predictive world simulators using frameworks like PyTorch or JAX — you have shipped these systems, not just studied them Strong foundation in deep learning architectures relevant to world modeling: transformers, diffusion models, neural radiance fields (NeRF), and variational recurrent state-space models Proficient in Python as a primary research and development language, with production-level familiarity in C++ for latency-sensitive inference and real-time robotics integration Experience with robotics middleware and simulation environments — ROS2, Isaac Sim, MuJoCo — and the ability to close the sim-to-real gap in learned representations Experience with video prediction or future-frame generation models (e.g., RSSM, DreamerV3, UniSim, Genie) is a strong plus Able to read and implement from recent arXiv papers with minimal overhead — you are comfortable turning a research prototype into a tested, integrated system

Responsibilities

This role is dedicated to architecting the internal world models that serve as the cognitive backbone for a general-purpose humanoid robot, enabling it to plan, predict, and adapt in physical environments. The engineer will directly shape the core intelligence architecture to ensure the humanoid can generalize across unstructured and unpredictable real-world settings.