AI Engineer (World Models)

Foundation Robotics Labs Inc.; San Francisco (CA); On-site; USD 180,000 - 260,000; Full time

Job summary

Foundation Robotics Labs Inc. is seeking engineers and scientists to build a general-purpose humanoid with strong world models and cognitive backbones.

You will contribute to the internal models, plan, predict, and adapt to diverse environments while working closely with a team pushing the boundaries of robotics intelligence. We value hands-on experience with world modeling frameworks, Python and C++ for real-time robotics, and proficiency with ROS2 and MuJoCo/Isaac Sim for sim-to-real

Qualifications

• Candidates should demonstrate hands-on experience in world modeling and model-based RL.
• Strong Python skills with production-level C++ for latency-sensitive robotics tasks are preferred.
• Experience with robotics simulators and sim-to-real transfer is essential.

Responsibilities

• Architect and implement internal world models for a humanoid robot platform.
• Advance end-to-end simulation-to-real deployment with robust representations.
• Translate research into tested, integrated robotics software stacks.

Skills

World modeling

Model-based RL

Python programming

C++ robotics

Tools

PyTorch

JAX

ROS2

MuJoCo

Isaac Sim

Job description

Our mission is to create advanced robots that can operate in complex environments, reducing human risk in conflict zones and enhancing efficiency in labor-intensive industries.

We are on the lookout for extraordinary engineers and scientists to join our team.

Your previous experience in robotics isn't a prerequisite - it's your talent and determination that truly count.

We expect that many of our team members will bring diverse perspectives from various industries and fields. We are looking for individuals with a proven record of exceptional ability and a history of creating things that work.

Our Culture

We like to be frank and honest about who we are, so that people can decide for themselves if this is a culture they resonate with. Please read more about our culture here https://foundation.bot/culture.

About This Role

Why You Should Join

• You are highly technical - regardless of the role you are in. We are building technology; you need to understand technology well.
• You care about aesthetics and design inside out. If it's not the best product ever, it bothers you, and you need to "fix" it.
• You don't need someone to motivate you; you get things done.

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 syste